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Andreas Gammelgaard Damsbo 2026-02-23 13:22:52 +01:00
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inst/translations/translation_da.csv
View file

@ -5,7 +5,6 @@
"REDCap server export","Eksport fra REDCap server"
"Local or sample data","Lokal eller testdata"
"Please be mindfull handling sensitive data","Pas godt på og overvej nøje hvordan du håndterer personfølsomme data"
"The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).","***FreesearchR*** opbevarer alene data i forbindelse med din analyse, men du bør kun behandle personfølsomme data når du kører ***FreesearchR*** direkte på din egen maskine. [Læs mere her](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine)."
"Quick overview","Hurtigt overblik"
"Select variables for final import","Vælg variabler til den endelige import"
"Exclude incomplete variables:","Ekskluder inkomplette variabler:"
@ -24,16 +23,11 @@
"Apply filter on observation","Anvend filtre af observationer"
"Edit and create data","Ændr og opret variabler"
"Subset, rename and convert variables","Udvælg, omdøb og konverter variabler"
"Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.).","Nedenfor er der mulighed for at lave simple ændringer i dit datasæt, såsom at redigere variabelnavne eller beskrivelser (bedre tabeller), eller omklassificering af variabler (numerisk, factoriel/kategorisk)."
"Please note that data modifications are applied before any filtering.","Bemærk at alle ændringer i data anvendes inden filtreringen."
"Advanced data manipulation","Avanceret datamanipulation"
"Below options allow more advanced varaible manipulations.","Nedenfor er mulighed for avancerede ændringer i data."
"New factor","Ny faktor"
"Create factor/categorical variable from a continous variable (number/date/time).","Opret kategorisk variabel på baggrund af kontinuert variabel (numerisk/dato/tid)."
"New variable","Ny variabel"
"Create a new variable based on an R-expression.","Opret ny variabel baseret på R-kode."
"Compare modified data to original","Sammenlign ændret data med det originale datasæt"
"Raw print of the original vs the modified data.","Simpel sammenligning af det originale og det ændrede datasæt."
"Original data:","Original data:"
"Modified data:","Ændret data:"
"New column name:","Navn til ny variabel:"
@ -64,7 +58,6 @@
"Imported data","Importeret data"
"www/intro.md","www/intro.md"
"Choose your data","Vælg dine data"
"Upload a file, get data directly from REDCap or use local or sample data.","Upload en fil, hent data direkte fra en REDCap-server eller brug test-data eller lokal data."
"Factor variable to reorder:","Kategoriske variabel der skal ændres:"
"Sort by levels","Sorter efter niveauer"
"Sort by count","Sorter efter antal"
@ -95,9 +88,7 @@
"Visuals","Grafik"
"Regression","Regression"
"Download","Download"
"{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.","{data_text} har {n} observationer og {n_var} variabler, med {n_complete} ({p_complete} %) komplette cases."
"Prepare","Forbered"
"At 0, only complete variables are included; at 100, all variables are included.","Ved 0 inkluderes alene komplette variabler; ved 100 inkluderes alle variabler."
"The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.","De følgende variabel-par er stærkt korrelerede: {sentence_paste(.x,and_str)}.\nOvervej at fjerne en {more}fra datasættet for at sikre at prædiktorer er internt uafhængige."
"No variables have a correlation measure above the threshold.","Ingen variabler er korrelerede over den angivne tærskelværdi."
"and","og"
@ -141,23 +132,17 @@
"Create plot","Dan grafik"
"Coefficients plot","Koefficientgraf"
"Checks","Test af model"
"Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters.","Nedenfor er en opsummerende tabel, der giver hurtigt overblik. Til højre kan du få et visuelt overblik, gennemgå observationer og oprette datafiltre."
"Browse observations","Gennemse observationer"
"Settings","Indstillinger"
"The following error occured on determining correlations:","Følgende fejl opstod i forbindelse med korrelationsanalysen:"
"We encountered the following error creating your report:","Følgende fejl opstod, da rapporten blev dannet:"
"No missing observations","Ingen manglende observationer"
"There is a total of {p_miss} % missing observations.","Der er i alt {p_miss} % manglende observationer."
"Median:","Median:"
"Restore original data","Gendan originale data"
"Reset to original imported dataset. Careful! There is no un-doing.","Gendan det oprindeligt importerede datasæt. Forsigtig! Alle dine ændringer vil forsvinde."
"Characteristics","Karakteristika"
"Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list.","Alene kategoriske variabler kan danne grundlag for stratificering. Mangler du en variabel, så gå til ""Forbered"" og omklassificer til kategorisk."
"Compare strata?","Sammenlign strata?"
"Correlations","Korrelationer"
"To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.","For at udelukke svarvariablen fra korrelationsanalysen, så kan du vælge din svarvariabel eller vælge 'non', hvis du ikke vil angive en."
"Correlation cut-off","Korrelationsgrænse"
"Set the cut-off for considered 'highly correlated'.","Angiv grænsen for. hvad, der tolkes som 'betydelig korrelation'."
"Missings","Manglende observationer"
"Class","Klasse"
"Observations","Observationer"
@ -167,11 +152,9 @@
"Confirm","Bekræft"
"The filtered data","Filtreret data"
"Create new factor","Ny kategorisk variabel"
"This window is aimed at advanced users and require some *R*-experience!","Dette vindue er primært for avancerede brugere med nogen *R*-erfaring!"
"Create new variables","Opret nye variabler"
"Select data types to include","Vælg datatyper, der skal inkluderes"
"Uploaded data overview","Overblik over uploaded data"
"Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias.","Her har du en oversigt over hvordan data er blevet formateret, og hvor der er manglende observationer. Brug informationen til at overveje om manglende data mangler tilfældigt eller og der er et mønster, som kan være et udtryk for systematisk manglende data (observationsbias)."
"Specify covariables","Angiv kovariabler"
"If none are selected, all are included.","Hvis ingen er valgt inkluderes alle."
"Analyse","Analysér"
@ -209,7 +192,6 @@
"List of datasets...","Liste af datasæt..."
"No data selected!","Ingen data valgt!"
"No dataset here...","Ingen datasæt her..."
"Use a dataset from your environment or from the environment of a package.","Brug et datasæt fra dit lokale kodemiljø eller fra en tilgængelig pakke."
"Not a data.frame","Ikke en data.frame"
"Select source","Vælg datakilde"
"Select a data source:","Vælg datakilde:"
@ -229,7 +211,6 @@
"Multivariable regression model checks","Tests af multivariabel regressionsmodel"
"Grouped by {get_label(data,ter)}","Grupperet efter {get_label(data,ter)}"
"Option to perform statistical comparisons between strata in baseline table.","Mulighed for at udføre statistiske tests mellem strata i oversigtstabellen."
"Press 'Evaluate' to create the comparison table.","Tryk 'Evaluér' for at oprette en oversigtstabel."
"The data includes {n_col} variables. Please limit to 100.","Data indeholder {n_col} variabler. Begræns venligst til 100."
"Data import","Data import"
"Data import formatting","Formatering af data ved import"
@ -261,7 +242,6 @@
"By specified numbers","Efter specifikke værdier"
"By quantiles (groups of equal size)","I grupper af samme størrelse"
"By week number","Efter ugenummer alene"
"There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data.","Der er mere avancerede muligheder for at ændre kategoriske variable, oprette nye kategoriske variabler fra eksisterende data eller nye variable baseret på R-kode. Nederst kan du gendanne originale data."
"Split the variable","Opdel variablen"
"Original data","Oprindelige data"
"Preview of result","Forhåndsvisning af resultat"
@ -275,7 +255,6 @@
"Browse data preview","Forhåndsvisning af resultat"
"Split character string","Opdel tegnstreng"
"Split text","Opdel tekst"
"Split a text column by a recognised delimiter.","Ingen tegnvariabler med accepterede afgrænsere fundet."
"Split a character string by a common delimiter","Opdel en tekstkolonne med en fælles afgrænser"
"Apply split","Anvend opdeling"
"Stacked relative barplot","Stablet relativt søjlediagram"
@ -290,14 +269,10 @@
"Words","Ord"
"Shorten to first letters","Afkort til første bogstaver"
"Shorten to first words","Afkort til de første ord"
"Missings across variables by the variable **'{input$missings_var}'**","Manglende værdier på tværs af variablerne **'{input$missings_var}'**"
"Missing vs non-missing observations in the variable **'{input$missings_var}'**","Manglende vs. ikke-manglende observationer i variablen **'{input$missings_var}'**"
"Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random.","Evaluer manglende værdier ved enten at sammenligne manglende værdier på tværs af variabler (valgfrit grupperet efter en kategorisk eller dikotom variabel) eller sammenligne variabler grupperet efter manglende status (mangler eller ej) for en udfaldsvariabel. Hvis der er en signifikant forskel i manglende værdier, kan dette forårsage en bias i dine data, og det bør overvejes omhyggeligt at fortolke dataene og analyserne, da data muligvis ikke mangler tilfældigt."
"Calculating. Hold tight for a moment..","Beregner. Hold lige fast et øjeblik.."
"Overview of missing observations","Oversigt over manglende observationer"
"Analysis method for missingness overview","Analysemetode for oversigt over manglende indhold"
"Overview of missings across variables","Oversigt over mangler på tværs af variabler"
"Overview of difference in variables by missing status in outcome","Oversigt over forskel i variabler ved manglende status i resultat"
"Select a variable for grouped overview","Vælg en variabel til grupperet oversigt"
"Select outcome variable for overview","Vælg resultatvariabel for oversigt"
"No outcome measure chosen","Ingen resultatmål valgt"
@ -341,3 +316,14 @@
"Reorder factor levels","Omarranger niveauer"
"Modify factor levels","Modify factor levels"
"Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables."
"Start by loading data.","Start by loading data."
"Maximum number of observations:","Maximum number of observations:"
"setting to 0 includes all","setting to 0 includes all"
"Select a dataset from your environment or sample dataset from a package.","Select a dataset from your environment or sample dataset from a package."
"Select a sample dataset from a package.","Select a sample dataset from a package."
"Data ready to be imported!","Data ready to be imported!"
"Data has %s obs. of %s variables.","Data has %s obs. of %s variables."
"Data successfully imported!","Data successfully imported!"
"Click to see data","Click to see data"
"No data present.","No data present."
"You have provided a complete dataset with no missing values.","You have provided a complete dataset with no missing values."

1 en da
5 REDCap server export Eksport fra REDCap server
6 Local or sample data Lokal eller testdata
7 Please be mindfull handling sensitive data Pas godt på og overvej nøje hvordan du håndterer personfølsomme data
The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine). ***FreesearchR*** opbevarer alene data i forbindelse med din analyse, men du bør kun behandle personfølsomme data når du kører ***FreesearchR*** direkte på din egen maskine. [Læs mere her](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).
8 Quick overview Hurtigt overblik
9 Select variables for final import Vælg variabler til den endelige import
10 Exclude incomplete variables: Ekskluder inkomplette variabler:
23 Apply filter on observation Anvend filtre af observationer
24 Edit and create data Ændr og opret variabler
25 Subset, rename and convert variables Udvælg, omdøb og konverter variabler
Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.). Nedenfor er der mulighed for at lave simple ændringer i dit datasæt, såsom at redigere variabelnavne eller beskrivelser (bedre tabeller), eller omklassificering af variabler (numerisk, factoriel/kategorisk).
Please note that data modifications are applied before any filtering. Bemærk at alle ændringer i data anvendes inden filtreringen.
26 Advanced data manipulation Avanceret datamanipulation
27 Below options allow more advanced varaible manipulations. Nedenfor er mulighed for avancerede ændringer i data.
28 New factor Ny faktor
Create factor/categorical variable from a continous variable (number/date/time). Opret kategorisk variabel på baggrund af kontinuert variabel (numerisk/dato/tid).
29 New variable Ny variabel
Create a new variable based on an R-expression. Opret ny variabel baseret på R-kode.
30 Compare modified data to original Sammenlign ændret data med det originale datasæt
Raw print of the original vs the modified data. Simpel sammenligning af det originale og det ændrede datasæt.
31 Original data: Original data:
32 Modified data: Ændret data:
33 New column name: Navn til ny variabel:
58 Imported data Importeret data
59 www/intro.md www/intro.md
60 Choose your data Vælg dine data
Upload a file, get data directly from REDCap or use local or sample data. Upload en fil, hent data direkte fra en REDCap-server eller brug test-data eller lokal data.
61 Factor variable to reorder: Kategoriske variabel der skal ændres:
62 Sort by levels Sorter efter niveauer
63 Sort by count Sorter efter antal
88 Visuals Grafik
89 Regression Regression
90 Download Download
{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases. {data_text} har {n} observationer og {n_var} variabler, med {n_complete} ({p_complete} %) komplette cases.
91 Prepare Forbered
At 0, only complete variables are included; at 100, all variables are included. Ved 0 inkluderes alene komplette variabler; ved 100 inkluderes alle variabler.
92 The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent. De følgende variabel-par er stærkt korrelerede: {sentence_paste(.x,and_str)}.\nOvervej at fjerne en {more}fra datasættet for at sikre at prædiktorer er internt uafhængige.
93 No variables have a correlation measure above the threshold. Ingen variabler er korrelerede over den angivne tærskelværdi.
94 and og
132 Create plot Dan grafik
133 Coefficients plot Koefficientgraf
134 Checks Test af model
Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters. Nedenfor er en opsummerende tabel, der giver hurtigt overblik. Til højre kan du få et visuelt overblik, gennemgå observationer og oprette datafiltre.
135 Browse observations Gennemse observationer
136 Settings Indstillinger
137 The following error occured on determining correlations: Følgende fejl opstod i forbindelse med korrelationsanalysen:
We encountered the following error creating your report: Følgende fejl opstod, da rapporten blev dannet:
138 No missing observations Ingen manglende observationer
139 There is a total of {p_miss} % missing observations. Der er i alt {p_miss} % manglende observationer.
140 Median: Median:
141 Restore original data Gendan originale data
Reset to original imported dataset. Careful! There is no un-doing. Gendan det oprindeligt importerede datasæt. Forsigtig! Alle dine ændringer vil forsvinde.
142 Characteristics Karakteristika
Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list. Alene kategoriske variabler kan danne grundlag for stratificering. Mangler du en variabel, så gå til "Forbered" og omklassificer til kategorisk.
143 Compare strata? Sammenlign strata?
144 Correlations Korrelationer
To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'. For at udelukke svarvariablen fra korrelationsanalysen, så kan du vælge din svarvariabel eller vælge 'non', hvis du ikke vil angive en.
145 Correlation cut-off Korrelationsgrænse
Set the cut-off for considered 'highly correlated'. Angiv grænsen for. hvad, der tolkes som 'betydelig korrelation'.
146 Missings Manglende observationer
147 Class Klasse
148 Observations Observationer
152 Confirm Bekræft
153 The filtered data Filtreret data
154 Create new factor Ny kategorisk variabel
This window is aimed at advanced users and require some *R*-experience! Dette vindue er primært for avancerede brugere med nogen *R*-erfaring!
155 Create new variables Opret nye variabler
156 Select data types to include Vælg datatyper, der skal inkluderes
157 Uploaded data overview Overblik over uploaded data
Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias. Her har du en oversigt over hvordan data er blevet formateret, og hvor der er manglende observationer. Brug informationen til at overveje om manglende data mangler tilfældigt eller og der er et mønster, som kan være et udtryk for systematisk manglende data (observationsbias).
158 Specify covariables Angiv kovariabler
159 If none are selected, all are included. Hvis ingen er valgt inkluderes alle.
160 Analyse Analysér
192 List of datasets... Liste af datasæt...
193 No data selected! Ingen data valgt!
194 No dataset here... Ingen datasæt her...
Use a dataset from your environment or from the environment of a package. Brug et datasæt fra dit lokale kodemiljø eller fra en tilgængelig pakke.
195 Not a data.frame Ikke en data.frame
196 Select source Vælg datakilde
197 Select a data source: Vælg datakilde:
211 Multivariable regression model checks Tests af multivariabel regressionsmodel
212 Grouped by {get_label(data,ter)} Grupperet efter {get_label(data,ter)}
213 Option to perform statistical comparisons between strata in baseline table. Mulighed for at udføre statistiske tests mellem strata i oversigtstabellen.
Press 'Evaluate' to create the comparison table. Tryk 'Evaluér' for at oprette en oversigtstabel.
214 The data includes {n_col} variables. Please limit to 100. Data indeholder {n_col} variabler. Begræns venligst til 100.
215 Data import Data import
216 Data import formatting Formatering af data ved import
242 By specified numbers Efter specifikke værdier
243 By quantiles (groups of equal size) I grupper af samme størrelse
244 By week number Efter ugenummer alene
There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data. Der er mere avancerede muligheder for at ændre kategoriske variable, oprette nye kategoriske variabler fra eksisterende data eller nye variable baseret på R-kode. Nederst kan du gendanne originale data.
245 Split the variable Opdel variablen
246 Original data Oprindelige data
247 Preview of result Forhåndsvisning af resultat
255 Browse data preview Forhåndsvisning af resultat
256 Split character string Opdel tegnstreng
257 Split text Opdel tekst
Split a text column by a recognised delimiter. Ingen tegnvariabler med accepterede afgrænsere fundet.
258 Split a character string by a common delimiter Opdel en tekstkolonne med en fælles afgrænser
259 Apply split Anvend opdeling
260 Stacked relative barplot Stablet relativt søjlediagram
269 Words Ord
270 Shorten to first letters Afkort til første bogstaver
271 Shorten to first words Afkort til de første ord
Missings across variables by the variable **'{input$missings_var}'** Manglende værdier på tværs af variablerne **'{input$missings_var}'**
Missing vs non-missing observations in the variable **'{input$missings_var}'** Manglende vs. ikke-manglende observationer i variablen **'{input$missings_var}'**
Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random. Evaluer manglende værdier ved enten at sammenligne manglende værdier på tværs af variabler (valgfrit grupperet efter en kategorisk eller dikotom variabel) eller sammenligne variabler grupperet efter manglende status (mangler eller ej) for en udfaldsvariabel. Hvis der er en signifikant forskel i manglende værdier, kan dette forårsage en bias i dine data, og det bør overvejes omhyggeligt at fortolke dataene og analyserne, da data muligvis ikke mangler tilfældigt.
272 Calculating. Hold tight for a moment.. Beregner. Hold lige fast et øjeblik..
273 Overview of missing observations Oversigt over manglende observationer
274 Analysis method for missingness overview Analysemetode for oversigt over manglende indhold
275 Overview of missings across variables Oversigt over mangler på tværs af variabler
Overview of difference in variables by missing status in outcome Oversigt over forskel i variabler ved manglende status i resultat
276 Select a variable for grouped overview Vælg en variabel til grupperet oversigt
277 Select outcome variable for overview Vælg resultatvariabel for oversigt
278 No outcome measure chosen Ingen resultatmål valgt
316 Reorder factor levels Omarranger niveauer
317 Modify factor levels Modify factor levels
318 Reorder or rename the levels of factor/categorical variables. Reorder or rename the levels of factor/categorical variables.
319 Start by loading data. Start by loading data.
320 Maximum number of observations: Maximum number of observations:
321 setting to 0 includes all setting to 0 includes all
322 Select a dataset from your environment or sample dataset from a package. Select a dataset from your environment or sample dataset from a package.
323 Select a sample dataset from a package. Select a sample dataset from a package.
324 Data ready to be imported! Data ready to be imported!
325 Data has %s obs. of %s variables. Data has %s obs. of %s variables.
326 Data successfully imported! Data successfully imported!
327 Click to see data Click to see data
328 No data present. No data present.
329 You have provided a complete dataset with no missing values. You have provided a complete dataset with no missing values.

36
inst/translations/translation_sw.csv
View file

@ -5,7 +5,6 @@
"REDCap server export","Usafirishaji wa seva ya REDCap"
"Local or sample data","Data ya ndani au ya sampuli"
"Please be mindfull handling sensitive data","Tafadhali kuwa mwangalifu kushughulikia data nyeti"
"The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).","Programu ya ***FreesearchR*** huhifadhi data kwa ajili ya uchambuzi pekee, lakini tafadhali tumia tu na data nyeti unapoendesha ndani. [Soma zaidi hapa](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine)."
"Quick overview","Muhtasari wa haraka"
"Select variables for final import","Chagua vigezo vya kuingiza mwisho"
"Exclude incomplete variables:","Ondoa vigezo visivyokamilika:"
@ -24,16 +23,11 @@
"Apply filter on observation","Tumia kichujio wakati wa uchunguzi"
"Edit and create data","Hariri na uunde data"
"Subset, rename and convert variables","Weka sehemu ndogo, badilisha jina na ubadilishe vigezo"
"Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.).","Hapa chini, kuna chaguo kadhaa za urekebishaji rahisi wa data kama vile kusasisha vigezo kwa kubadilisha majina, kuunda lebo mpya (kwa majedwali mazuri zaidi katika ripoti) na kubadilisha madarasa ya vigezo (nambari, vipengele/kategoria n.k.)."
"Please note that data modifications are applied before any filtering.","Tafadhali kumbuka kwamba marekebisho ya data hutumika kabla ya kuchuja yoyote."
"Advanced data manipulation","Udhibiti wa data wa hali ya juu"
"Below options allow more advanced varaible manipulations.","Chaguzi zilizo hapa chini huruhusu udanganyifu wa hali ya juu zaidi unaoweza kubadilika."
"New factor","Kipengele kipya"
"Create factor/categorical variable from a continous variable (number/date/time).","Unda kigezo cha kipengele/kitengo kutoka kwa kigezo endelevu (nambari/tarehe/saa)."
"New variable","Kigezo kipya"
"Create a new variable based on an R-expression.","Unda kigezo kipya kulingana na usemi wa R."
"Compare modified data to original","Linganisha data iliyobadilishwa na ya asili"
"Raw print of the original vs the modified data.","Chapisho ghafi la data asili dhidi ya data iliyorekebishwa."
"Original data:","Data asilia:"
"Modified data:","Data iliyorekebishwa:"
"New column name:","Jina jipya la safu wima:"
@ -64,7 +58,6 @@
"Imported data","Data iliyoingizwa"
"www/intro.md","www/intro.md"
"Choose your data","Chagua data yako"
"Upload a file, get data directly from REDCap or use local or sample data.","Pakia faili, pata data moja kwa moja kutoka REDCap au tumia data ya ndani au sampuli."
"Factor variable to reorder:","Kigezo cha vipengele ili kupanga upya:"
"Sort by levels","Panga kwa viwango"
"Sort by count","Panga kwa hesabu"
@ -95,9 +88,7 @@
"Visuals","Picha"
"Regression","Urejeshaji"
"Download","Pakua"
"{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.","{data_text} ina uchunguzi wa {n} na vigezo vya {n_var}, pamoja na visa kamili vya {n_complete} ({p_complete}%)."
"Prepare","Tayarisha"
"At 0, only complete variables are included; at 100, all variables are included.","Katika 0, ni vigezo kamili pekee vilivyojumuishwa; katika 100, vigezo vyote vimejumuishwa."
"The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.","Jozi zifuatazo za vigeu zina uhusiano wa hali ya juu: {sentence_paste(.x,and_str)}.\nFikiria kutenga moja {zaidi} kutoka kwenye seti ya data ili kuhakikisha vigeu vinajitegemea."
"No variables have a correlation measure above the threshold.","Hakuna vigezo vyenye kipimo cha uhusiano kilicho juu ya kizingiti."
"and","na"
@ -141,23 +132,17 @@
"Create plot","Unda njama"
"Coefficients plot","Mchoro wa viambato"
"Checks","Hundi"
"Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters.","Hapa chini kuna jedwali la muhtasari kwa ajili ya ufahamu wa haraka, na upande wa kulia unaweza kuibua madarasa ya data, kuvinjari uchunguzi na kutumia vichujio tofauti vya data."
"Browse observations","Vinjari uchunguzi"
"Settings","Mipangilio"
"The following error occured on determining correlations:","Hitilafu ifuatayo ilitokea katika kubaini uhusiano:"
"We encountered the following error creating your report:","Tulikutana na hitilafu ifuatayo katika kuunda ripoti yako:"
"No missing observations","Hakuna uchunguzi unaokosekana"
"There is a total of {p_miss} % missing observations.","Kuna jumla ya uchunguzi wa {p_miss}% unaokosekana."
"Median:","Wastani:"
"Restore original data","Rejesha data asili"
"Reset to original imported dataset. Careful! There is no un-doing.","Rudisha kwenye seti ya data asili iliyoingizwa. Kuwa mwangalifu! Hakuna kutengua."
"Characteristics","Sifa"
"Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list.","Vigezo vya vipengele/kategoria pekee ndivyo vinavyopatikana kwa ajili ya uainishaji wa tabaka. Rudi kwenye kichupo cha 'Tayarisha' ili kupanga upya kigezo ikiwa hakipo kwenye orodha."
"Compare strata?","Linganisha tabaka?"
"Correlations","Uhusiano"
"To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.","Ili kuepuka kutathmini uhusiano wa kigezo cha matokeo, hii inaweza kutengwa kwenye njama au kuchagua 'hakuna'."
"Correlation cut-off","Kikomo cha uhusiano"
"Set the cut-off for considered 'highly correlated'.","Weka kikomo cha 'kinachohusiana sana'."
"Missings","Hazipo"
"Class","Darasa"
"Observations","Uchunguzi"
@ -167,11 +152,9 @@
"Confirm","Thibitisha"
"The filtered data","Data iliyochujwa"
"Create new factor","Unda kipengele kipya"
"This window is aimed at advanced users and require some *R*-experience!","Dirisha hili linalenga watumiaji wa hali ya juu na linahitaji uzoefu wa *R*!"
"Create new variables","Unda vigezo vipya"
"Select data types to include","Chagua aina za data za kujumuisha"
"Uploaded data overview","Muhtasari wa data iliyopakiwa"
"Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias.","Hapa kuna muhtasari wa jinsi data yako inavyotafsiriwa, na mahali ambapo data inakosekana. Tumia taarifa hii kuzingatia ikiwa data inakosekana bila mpangilio au ikiwa baadhi ya uchunguzi unakosekana kimfumo ambao unaweza kusababishwa na upendeleo wa uchunguzi."
"Specify covariables","Bainisha vigeu vinavyoweza kuunganishwa"
"If none are selected, all are included.","Ikiwa hakuna aliyechaguliwa, wote wamejumuishwa."
"Analyse","Changanua"
@ -209,7 +192,6 @@
"List of datasets...","Orodha ya seti za data..."
"No data selected!","Hakuna data iliyochaguliwa!"
"No dataset here...","Hakuna seti ya data hapa..."
"Use a dataset from your environment or from the environment of a package.","Tumia seti ya data kutoka kwa mazingira yako au kutoka kwa mazingira ya kifurushi."
"Not a data.frame","Sio data.frame"
"Select source","Chagua chanzo"
"Select a data source:","Chagua chanzo cha data:"
@ -229,7 +211,6 @@
"Multivariable regression model checks","Ukaguzi wa modeli ya urejeshaji unaoweza kubadilika-badilika"
"Grouped by {get_label(data,ter)}","Imepangwa kwa makundi kulingana na {get_label(data,ter)}"
"Option to perform statistical comparisons between strata in baseline table.","Chaguo la kufanya ulinganisho wa takwimu kati ya tabaka katika jedwali la msingi."
"Press 'Evaluate' to create the comparison table.","Bonyeza 'Tathmini' ili kuunda jedwali la kulinganisha."
"The data includes {n_col} variables. Please limit to 100.","Data inajumuisha vigezo vya {n_col}. Tafadhali punguza hadi 100."
"Data import","Uingizaji wa data"
"Data import formatting","Uumbizaji wa kuingiza data"
@ -261,7 +242,6 @@
"By specified numbers","Kwa nambari zilizoainishwa"
"By quantiles (groups of equal size)","Kwa quantiles (vikundi vya ukubwa sawa)"
"Please fill in web address and API token, then press 'Connect'.","Tafadhali jaza anwani ya wavuti na tokeni ya API, kisha bonyeza 'Unganisha'."
"There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data.","Kuna chaguo za hali ya juu zaidi za kurekebisha vigezo vya vipengele/kategoria pamoja na kuunda kipengele kipya kutoka kwa kigezo kilichopo au vigezo vipya vyenye msimbo wa R. Chini unaweza kurejesha data asili."
"Text or character to split string by","Maandishi au herufi ya kugawanya mfuatano kwa"
"Split the variable","Gawanya kigezo"
"Variable to split:","Kinachoweza kubadilika hadi kugawanyika:"
@ -276,7 +256,6 @@
"Original data","Data asili"
"Preview of result","Hakikisho la matokeo"
"No character variables with accepted delimiters detected.","Hakuna vigezo vya herufi vilivyo na vidhibiti vinavyokubalika vilivyogunduliwa."
"Split a text column by a recognised delimiter.","Gawanya safu wima ya maandishi kwa kitenga kinachotambulika."
"Apply split","Tumia mgawanyiko"
"Stacked relative barplot","Kipande cha baruni kilichopangwa kwa mirundiko"
"Create relative stacked barplots to show the distribution of categorical levels","Unda viwanja vya baruni vilivyopangwa ili kuonyesha usambazaji wa viwango vya kategoria"
@ -290,14 +269,10 @@
"Words","Maneno"
"Shorten to first letters","Fupisha herufi za kwanza"
"Shorten to first words","Fupisha maneno ya kwanza"
"Missings across variables by the variable **'{input$missings_var}'**","Hazipo katika vigezo kwa kigezo **'{input$missings_var}'**"
"Missing vs non-missing observations in the variable **'{input$missings_var}'**","Uchunguzi unaokosekana dhidi ya usiokosekana katika kigezo **'{input$missings_var}'**"
"Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random.","Tathmini upungufu kwa kulinganisha thamani zinazokosekana katika vigezo (hiari zilizopangwa kwa mujibu wa kigezo cha kategoria au cha pande mbili) au linganisha vigezo vilivyopangwa kwa mujibu wa hali inayokosekana (inayokosekana au isiyokosekana) ya kigezo cha matokeo. Ikiwa kuna tofauti kubwa katika upungufu, hii inaweza kusababisha upendeleo katika data yako na inapaswa kuzingatiwa kwa uangalifu kutafsiri data na uchambuzi kwani data inaweza isikosekane bila mpangilio."
"Calculating. Hold tight for a moment..","Kuhesabu. Shikilia kwa muda.."
"Overview of missing observations","Muhtasari wa uchunguzi uliokosekana"
"Analysis method for missingness overview","Mbinu ya uchambuzi wa muhtasari wa kukosekana"
"Overview of missings across variables","Muhtasari wa mambo yanayokosekana katika vigezo"
"Overview of difference in variables by missing status in outcome","Muhtasari wa tofauti katika vigezo kwa kukosa hali katika matokeo"
"Select a variable for grouped overview","Chagua kigezo cha muhtasari wa kikundi"
"Select outcome variable for overview","Chagua kigezo cha matokeo kwa muhtasari"
"No outcome measure chosen","Hakuna kipimo cha matokeo kilichochaguliwa"
@ -341,3 +316,14 @@
"Reorder factor levels","Reorder factor levels"
"Modify factor levels","Modify factor levels"
"Reorder or rename the levels of factor/categorical variables.","Reorder or rename the levels of factor/categorical variables."
"Start by loading data.","Start by loading data."
"Maximum number of observations:","Maximum number of observations:"
"setting to 0 includes all","setting to 0 includes all"
"Select a dataset from your environment or sample dataset from a package.","Select a dataset from your environment or sample dataset from a package."
"Select a sample dataset from a package.","Select a sample dataset from a package."
"Data ready to be imported!","Data ready to be imported!"
"Data has %s obs. of %s variables.","Data has %s obs. of %s variables."
"Data successfully imported!","Data successfully imported!"
"Click to see data","Click to see data"
"No data present.","No data present."
"You have provided a complete dataset with no missing values.","You have provided a complete dataset with no missing values."

1 en sw
5 REDCap server export Usafirishaji wa seva ya REDCap
6 Local or sample data Data ya ndani au ya sampuli
7 Please be mindfull handling sensitive data Tafadhali kuwa mwangalifu kushughulikia data nyeti
The ***FreesearchR*** app only stores data for analyses, but please only use with sensitive data when running locally. [Read more here](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine). Programu ya ***FreesearchR*** huhifadhi data kwa ajili ya uchambuzi pekee, lakini tafadhali tumia tu na data nyeti unapoendesha ndani. [Soma zaidi hapa](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).
8 Quick overview Muhtasari wa haraka
9 Select variables for final import Chagua vigezo vya kuingiza mwisho
10 Exclude incomplete variables: Ondoa vigezo visivyokamilika:
23 Apply filter on observation Tumia kichujio wakati wa uchunguzi
24 Edit and create data Hariri na uunde data
25 Subset, rename and convert variables Weka sehemu ndogo, badilisha jina na ubadilishe vigezo
Below, are several options for simple data manipulation like update variables by renaming, creating new labels (for nicer tables in the report) and changing variable classes (numeric, factor/categorical etc.). Hapa chini, kuna chaguo kadhaa za urekebishaji rahisi wa data kama vile kusasisha vigezo kwa kubadilisha majina, kuunda lebo mpya (kwa majedwali mazuri zaidi katika ripoti) na kubadilisha madarasa ya vigezo (nambari, vipengele/kategoria n.k.).
Please note that data modifications are applied before any filtering. Tafadhali kumbuka kwamba marekebisho ya data hutumika kabla ya kuchuja yoyote.
26 Advanced data manipulation Udhibiti wa data wa hali ya juu
27 Below options allow more advanced varaible manipulations. Chaguzi zilizo hapa chini huruhusu udanganyifu wa hali ya juu zaidi unaoweza kubadilika.
28 New factor Kipengele kipya
Create factor/categorical variable from a continous variable (number/date/time). Unda kigezo cha kipengele/kitengo kutoka kwa kigezo endelevu (nambari/tarehe/saa).
29 New variable Kigezo kipya
Create a new variable based on an R-expression. Unda kigezo kipya kulingana na usemi wa R.
30 Compare modified data to original Linganisha data iliyobadilishwa na ya asili
Raw print of the original vs the modified data. Chapisho ghafi la data asili dhidi ya data iliyorekebishwa.
31 Original data: Data asilia:
32 Modified data: Data iliyorekebishwa:
33 New column name: Jina jipya la safu wima:
58 Imported data Data iliyoingizwa
59 www/intro.md www/intro.md
60 Choose your data Chagua data yako
Upload a file, get data directly from REDCap or use local or sample data. Pakia faili, pata data moja kwa moja kutoka REDCap au tumia data ya ndani au sampuli.
61 Factor variable to reorder: Kigezo cha vipengele ili kupanga upya:
62 Sort by levels Panga kwa viwango
63 Sort by count Panga kwa hesabu
88 Visuals Picha
89 Regression Urejeshaji
90 Download Pakua
{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases. {data_text} ina uchunguzi wa {n} na vigezo vya {n_var}, pamoja na visa kamili vya {n_complete} ({p_complete}%).
91 Prepare Tayarisha
At 0, only complete variables are included; at 100, all variables are included. Katika 0, ni vigezo kamili pekee vilivyojumuishwa; katika 100, vigezo vyote vimejumuishwa.
92 The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent. Jozi zifuatazo za vigeu zina uhusiano wa hali ya juu: {sentence_paste(.x,and_str)}.\nFikiria kutenga moja {zaidi} kutoka kwenye seti ya data ili kuhakikisha vigeu vinajitegemea.
93 No variables have a correlation measure above the threshold. Hakuna vigezo vyenye kipimo cha uhusiano kilicho juu ya kizingiti.
94 and na
132 Create plot Unda njama
133 Coefficients plot Mchoro wa viambato
134 Checks Hundi
Below you find a summary table for quick insigths, and on the right you can visualise data classes, browse observations and apply different data filters. Hapa chini kuna jedwali la muhtasari kwa ajili ya ufahamu wa haraka, na upande wa kulia unaweza kuibua madarasa ya data, kuvinjari uchunguzi na kutumia vichujio tofauti vya data.
135 Browse observations Vinjari uchunguzi
136 Settings Mipangilio
137 The following error occured on determining correlations: Hitilafu ifuatayo ilitokea katika kubaini uhusiano:
We encountered the following error creating your report: Tulikutana na hitilafu ifuatayo katika kuunda ripoti yako:
138 No missing observations Hakuna uchunguzi unaokosekana
139 There is a total of {p_miss} % missing observations. Kuna jumla ya uchunguzi wa {p_miss}% unaokosekana.
140 Median: Wastani:
141 Restore original data Rejesha data asili
Reset to original imported dataset. Careful! There is no un-doing. Rudisha kwenye seti ya data asili iliyoingizwa. Kuwa mwangalifu! Hakuna kutengua.
142 Characteristics Sifa
Only factor/categorical variables are available for stratification. Go back to the 'Prepare' tab to reclass a variable if it's not on the list. Vigezo vya vipengele/kategoria pekee ndivyo vinavyopatikana kwa ajili ya uainishaji wa tabaka. Rudi kwenye kichupo cha 'Tayarisha' ili kupanga upya kigezo ikiwa hakipo kwenye orodha.
143 Compare strata? Linganisha tabaka?
144 Correlations Uhusiano
To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'. Ili kuepuka kutathmini uhusiano wa kigezo cha matokeo, hii inaweza kutengwa kwenye njama au kuchagua 'hakuna'.
145 Correlation cut-off Kikomo cha uhusiano
Set the cut-off for considered 'highly correlated'. Weka kikomo cha 'kinachohusiana sana'.
146 Missings Hazipo
147 Class Darasa
148 Observations Uchunguzi
152 Confirm Thibitisha
153 The filtered data Data iliyochujwa
154 Create new factor Unda kipengele kipya
This window is aimed at advanced users and require some *R*-experience! Dirisha hili linalenga watumiaji wa hali ya juu na linahitaji uzoefu wa *R*!
155 Create new variables Unda vigezo vipya
156 Select data types to include Chagua aina za data za kujumuisha
157 Uploaded data overview Muhtasari wa data iliyopakiwa
Here is an overview of how your data is interpreted, and where data is missing. Use this information to consider if data is missing at random or if some observations are missing systematically wich may be caused by an observation bias. Hapa kuna muhtasari wa jinsi data yako inavyotafsiriwa, na mahali ambapo data inakosekana. Tumia taarifa hii kuzingatia ikiwa data inakosekana bila mpangilio au ikiwa baadhi ya uchunguzi unakosekana kimfumo ambao unaweza kusababishwa na upendeleo wa uchunguzi.
158 Specify covariables Bainisha vigeu vinavyoweza kuunganishwa
159 If none are selected, all are included. Ikiwa hakuna aliyechaguliwa, wote wamejumuishwa.
160 Analyse Changanua
192 List of datasets... Orodha ya seti za data...
193 No data selected! Hakuna data iliyochaguliwa!
194 No dataset here... Hakuna seti ya data hapa...
Use a dataset from your environment or from the environment of a package. Tumia seti ya data kutoka kwa mazingira yako au kutoka kwa mazingira ya kifurushi.
195 Not a data.frame Sio data.frame
196 Select source Chagua chanzo
197 Select a data source: Chagua chanzo cha data:
211 Multivariable regression model checks Ukaguzi wa modeli ya urejeshaji unaoweza kubadilika-badilika
212 Grouped by {get_label(data,ter)} Imepangwa kwa makundi kulingana na {get_label(data,ter)}
213 Option to perform statistical comparisons between strata in baseline table. Chaguo la kufanya ulinganisho wa takwimu kati ya tabaka katika jedwali la msingi.
Press 'Evaluate' to create the comparison table. Bonyeza 'Tathmini' ili kuunda jedwali la kulinganisha.
214 The data includes {n_col} variables. Please limit to 100. Data inajumuisha vigezo vya {n_col}. Tafadhali punguza hadi 100.
215 Data import Uingizaji wa data
216 Data import formatting Uumbizaji wa kuingiza data
242 By specified numbers Kwa nambari zilizoainishwa
243 By quantiles (groups of equal size) Kwa quantiles (vikundi vya ukubwa sawa)
244 Please fill in web address and API token, then press 'Connect'. Tafadhali jaza anwani ya wavuti na tokeni ya API, kisha bonyeza 'Unganisha'.
There are more advanced options to modify factor/categorical variables as well as create new factor from an existing variable or new variables with R code. At the bottom you can restore the original data. Kuna chaguo za hali ya juu zaidi za kurekebisha vigezo vya vipengele/kategoria pamoja na kuunda kipengele kipya kutoka kwa kigezo kilichopo au vigezo vipya vyenye msimbo wa R. Chini unaweza kurejesha data asili.
245 Text or character to split string by Maandishi au herufi ya kugawanya mfuatano kwa
246 Split the variable Gawanya kigezo
247 Variable to split: Kinachoweza kubadilika hadi kugawanyika:
256 Original data Data asili
257 Preview of result Hakikisho la matokeo
258 No character variables with accepted delimiters detected. Hakuna vigezo vya herufi vilivyo na vidhibiti vinavyokubalika vilivyogunduliwa.
Split a text column by a recognised delimiter. Gawanya safu wima ya maandishi kwa kitenga kinachotambulika.
259 Apply split Tumia mgawanyiko
260 Stacked relative barplot Kipande cha baruni kilichopangwa kwa mirundiko
261 Create relative stacked barplots to show the distribution of categorical levels Unda viwanja vya baruni vilivyopangwa ili kuonyesha usambazaji wa viwango vya kategoria
269 Words Maneno
270 Shorten to first letters Fupisha herufi za kwanza
271 Shorten to first words Fupisha maneno ya kwanza
Missings across variables by the variable **'{input$missings_var}'** Hazipo katika vigezo kwa kigezo **'{input$missings_var}'**
Missing vs non-missing observations in the variable **'{input$missings_var}'** Uchunguzi unaokosekana dhidi ya usiokosekana katika kigezo **'{input$missings_var}'**
Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random. Tathmini upungufu kwa kulinganisha thamani zinazokosekana katika vigezo (hiari zilizopangwa kwa mujibu wa kigezo cha kategoria au cha pande mbili) au linganisha vigezo vilivyopangwa kwa mujibu wa hali inayokosekana (inayokosekana au isiyokosekana) ya kigezo cha matokeo. Ikiwa kuna tofauti kubwa katika upungufu, hii inaweza kusababisha upendeleo katika data yako na inapaswa kuzingatiwa kwa uangalifu kutafsiri data na uchambuzi kwani data inaweza isikosekane bila mpangilio.
272 Calculating. Hold tight for a moment.. Kuhesabu. Shikilia kwa muda..
273 Overview of missing observations Muhtasari wa uchunguzi uliokosekana
274 Analysis method for missingness overview Mbinu ya uchambuzi wa muhtasari wa kukosekana
275 Overview of missings across variables Muhtasari wa mambo yanayokosekana katika vigezo
Overview of difference in variables by missing status in outcome Muhtasari wa tofauti katika vigezo kwa kukosa hali katika matokeo
276 Select a variable for grouped overview Chagua kigezo cha muhtasari wa kikundi
277 Select outcome variable for overview Chagua kigezo cha matokeo kwa muhtasari
278 No outcome measure chosen Hakuna kipimo cha matokeo kilichochaguliwa
316 Reorder factor levels Reorder factor levels
317 Modify factor levels Modify factor levels
318 Reorder or rename the levels of factor/categorical variables. Reorder or rename the levels of factor/categorical variables.
319 Start by loading data. Start by loading data.
320 Maximum number of observations: Maximum number of observations:
321 setting to 0 includes all setting to 0 includes all
322 Select a dataset from your environment or sample dataset from a package. Select a dataset from your environment or sample dataset from a package.
323 Select a sample dataset from a package. Select a sample dataset from a package.
324 Data ready to be imported! Data ready to be imported!
325 Data has %s obs. of %s variables. Data has %s obs. of %s variables.
326 Data successfully imported! Data successfully imported!
327 Click to see data Click to see data
328 No data present. No data present.
329 You have provided a complete dataset with no missing values. You have provided a complete dataset with no missing values.