FreesearchR/inst/translations/translation_da.csv

1	en	da
2	Hello	Hej
3	Get started	Kom i gang
4	File upload	Upload fil
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
8	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).
9	Quick overview	Hurtigt overblik
10	Select variables for final import	Vælg variabler til den endelige import
11	Exclude incomplete variables:	Ekskluder inkomplette variabler:
12	Manual selection:	Manuel udvælgelse:
13	Let's begin!	Kom i gang!
14	Analysis validation	Analysevalidering
15	Report	Rapport
16	Choose your favourite output file format for further work, and download, when the analyses are done.	Vælge dit foretrukne dataformat, og hent data, når du er ærdig med databehandlingen.
17	www/intro.html	www/intro_da.html
18	<p>The <em><strong>FreesearchR</strong></em> app only stores data for analyses, but please only use with sensitive data when running locally. <a href='https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine'>Read more here</a></p>	<p><em><strong>FreesearchR</strong></em> opbevarer alene data i forbindelse med din analyse, men du bør kun behandle personfølsomme data når du kører <em><strong>FreesearchR</strong></em> direkte på dine egen maskine. <a href='https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine'>Læs mere her</a></p>
19	Overview and filter	Overblik og filtre
20	Overview and filtering	Overblik og filtrering
21	Visual overview	Visuelt overblik
22	Filter data types	Filtrer datatyper
23	Filter observations	Filtrer observationer
24	Apply filter on observation	Anvend filtre af observationer
25	Edit and create data	Ændr og opret variabler
26	Subset, rename and convert variables	Udvælg, omdøb og konverter variabler
27	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).
28	There are more advanced options to modify factor/categorical variables as well as create new factor from a continous variable or new variables with R code. At the bottom you can restore the original data.	Her er mere avancerede muligheder for at ændre faktorielle/kategoriske data, danne nye faktorielle variabler fra kontinuerte eller komplet nye baseret på R-kode. Nederst har du mulighed for at gendanne data.
29	Please note that data modifications are applied before any filtering.	Bemærk at alle ændringer i data anvendes inden filtreringen.
30	Advanced data manipulation	Avanceret datamanipulation
31	Below options allow more advanced varaible manipulations.	Nedenfor er mulighed for avancerede ændringer i data.
32	Reorder factor levels	Arranger niveuer i faktor
33	Reorder the levels of factor/categorical variables.	Arranger rækkefølgen af niveauer i faktorielle/kategoriske variabler.
34	New factor	Ny faktor
35	Create factor/categorical variable from a continous variable (number/date/time).	Opret kategorisk variabel på baggrund af kontinuert variabel (numerisk/dato/tid).
36	New variable	Ny variabel
37	Create a new variable based on an R-expression.	Opret ny variabel baseret på R-kode.
38	Compare modified data to original	Sammenlign ændret data med det originale datasæt
39	Raw print of the original vs the modified data.	Simpel sammenligning af det originale og det ændrede datasæt.
40	Original data:	Original data:
41	Modified data:	Ændret data:
42	New column name:	Navn til ny variabel:
43	Group calculation by:	Grupper udregningen efter:
44	Enter an expression to define new column:	Indtast udregningen til at definere en ny variabel:
45	Click on a column name to add it to the expression:	Tryk på et variabel navn for at tilføje det til udregningen:
46	Create column	Opret variabel
47	New column name cannot be empty	Det nye variabelnavn kan ikke være tomt
48	Create a new column	Opret ny variabel
49	Some operations are not allowed	Nogle beregninger er ikke tilladte
50	Column added!	Variabel oprettet!
51	Unique values:	Unikke værdier:
52	Variable to cut:	Variabel, der skal deles:
53	Number of breaks:	Antal niveauer:
54	Close intervals on the right	Luk intervaller til højre
55	Include lowest value	Inkluderer den laveste værdi
56	Create factor variable	Opret kategorisk variabel
57	Fixed breaks:	Faste niveauer:
58	Method:	Metode:
59	Convert Numeric to Factor	Konverter numerisk til kategorisk
60	Unique:	Unique:
61	Missing:	Manglende:
62	Most Common:	Mest hyppige:
63	Min:	Min:
64	Mean:	Mean:
65	Max:	Max:
66	Decimal separator:	Decimal adskiller:
67	First five rows are shown below:	De første fem rækker vises nedenfor:
68	Imported data	Importeret data
69	www/intro.md	www/intro.md
70	Choose your data	Vælg dine data
71	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.
72	Factor variable to reorder:	Kategoriske variabel der skal ændres:
73	Sort by levels	Sorter efter niveauer
74	Sort by count	Sorter efter antal
75	Create a new variable (otherwise replaces the one selected)	Opret en ny variabel (ellers erstattes den oprindelige)
76	Update factor variable	Updater faktor-variabel
77	Sort count	Sorter antal
78	Levels	Niveauer
79	Count	Antal
80	Update levels of a factor	Updater niveauerne for en faktor
81	Update & select variables	Opdater og vælg variabler
82	Date format:	Datoformat:
83	Date to use as origin to convert date/datetime:	Dato, der skal anvendes som udgangspunkt for konvertering af dato/datotid:
84	Apply changes	Anvend ændringer
85	No data to display.	Ingen data at vise.
86	Data successfully updated!	Data er opdateret!
87	You removed {p_out} % of observations.	Du har fjernet {p_out} % af observationerne.
88	You removed {p_out} % of variables.	Du har fjernet {p_out} % af variablerne.
89	You can import {file_extensions_text} files	Du kan vælge mellem disse filtyper: {file_extensions_text}
90	You can choose between these file types:	Du kan vælge mellem følgene filtyper:
91	Rows to skip before reading data:	Rækker der skal springes over:
92	Missing values character(s):	Tegn for manglende værdier:
93	if several use a comma (',') to separate them	hvis flere, så anvend et komma (',') som seperator
94	Encoding:	Kodning:
95	Upload a file:	Upload en fil:
96	Browse...	Vælg...
97	Select sheet to import:	Vælg ark:
98	No file selected.	Ingen fil valgt.
99	Evaluate	Evaluer
100	Visuals	Grafik
101	Regression	Regression
102	Download	Download
103	{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.
104	Prepare	Forbered
105	At 0, only complete variables are included; at 100, all variables are included.	Ved 0 inkluderes alene komplette variabler; ved 100 inkluderes alle variabler.
106	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.
107	No variables have a correlation measure above the threshold.	Ingen variabler er korrelerede over den angivne tærskelværdi.
108	and	og
109	from each pair	fra hvert par
110	Only non-text variables are available for plotting. Go the "Data" to reclass data to plot.	Kun variabler, der ikke er klassificerede som tekst er tilgængelige. Gå til fanen "Forbered" for at ændre klassifikationer.
111	Plot	Tegn
112	Adjust settings, then press "Plot".	Juster indstillingerne og tryk så "Tegn".
113	Plot height (mm)	Højde af grafik (mm)
114	Plot width (mm)	Bredde af grafik (mm)
115	File format	File format
116	Download plot	Download grafik
117	Select variable	Vælg variabel
118	Response variable	Svarvariable
119	Plot type	Type af grafik
120	Please select	Vælg
121	Additional variables	Yderligere variabler
122	Secondary variable	Sekundær variabel
123	No variable	Ingen variabel
124	Grouping variable	Variabel til gruppering
125	No stratification	Ingen stratificering
126	Drawing the plot. Hold tight for a moment..	Tegner grafikken. Spænd selen..
127	#Plotting\n	#Tegner\n
128	Stacked horizontal bars	Stablede horisontale søjler
129	A classical way of visualising the distribution of an ordinal scale like the modified Ranking Scale and known as Grotta bars	En klassisk visualisering af fordelingen af observationer på en ordinal kategorisk skala. Typisk brugt til modified Rankin Scale og kendes også som 'Grotta bars'
130	Violin plot	Violin-diagram
131	A modern alternative to the classic boxplot to visualise data distribution	Moderne alternativ til den klassiske box-plot og velegnet til at visualisere fordelingen af observationer
132	Sankey plot	Sankey-diagram
133	A way of visualising change between groups	Visualiserer ændring mellem grupper for samme type observationer
134	Scatter plot	Punkt-diagram
135	A classic way of showing the association between to variables	Visualiserer forholdet mellem to variabler
136	Box plot	Kasse-diagram
137	A classic way to plot data distribution by groups	Klassik måde at visualisere fordeling
138	Euler diagram	Eulerdiagram
139	Generate area-proportional Euler diagrams to display set relationships	Generer proportionelt Euler-diagram for at vise forhold mellem forskellige kategoriske observationer
140	Documentation	Dokumentation
141	Data is only stored for analyses and deleted when the app is closed.	Data opbevares alene til brug i analyser og slettes så snart appen lukkes.
142	Consider [running ***FreesearchR*** locally](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine) if working with sensitive data.	Overvej at [køre ***FreesearchR*** lokalt](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine) hvis du arbejder med personfølsomme data.
143	Feedback	Feedback
144	License: AGPLv3	Licens: AGPLv3
145	Source	Kilde
146	Data includes {n_pairs} pairs of highly correlated variables.	Der er {n_pairs} variabel-par, der er stærkt internt korrelerede.
147	Create plot	Dan grafik
148	Coefficients plot	Koefficientgraf
149	Checks	Test af model
150	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.
151	Browse observations	Gennemse observationer
152	Settings	Indstillinger
153	The following error occured on determining correlations:	Følgende fejl opstod i forbindelse med korrelationsanalysen:
154	We encountered the following error creating your report:	Følgende fejl opstod, da rapporten blev dannet:
155	No variable chosen for analysis	Ingen variabel er valgt til analysen
156	No missing observations	Ingen manglende observationer
157	Missing vs non-missing observations in the variable **'{variabler()}'**	Manglende vs ikke-manglende observationer i variablen **'{variabler()}'**
158	There is a significant correlation between {n_nonmcar} variables and missing observations in the outcome variable {outcome}.	Der er en betydelig korrelation blandt {n_nonmcar} variabler sammenlignet efter manglende observationer i {outcome}.
159	There is a total of {p_miss} % missing observations.	Der er i alt {p_miss} % manglende observationer.
160	Median:	Median:
161	Restore original data	Gendan originale data
162	Reset to original imported dataset. Careful! There is no un-doing.	Gendan det oprindeligt importerede datasæt. Forsigtig! Alle dine ændringer vil forsvinde.
163	Characteristics	Karakteristika
164	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.
165	Compare strata?	Sammenlign strata?
166	Correlations	Korrelationer
167	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.
168	Correlation cut-off	Korrelationsgrænse
169	Set the cut-off for considered 'highly correlated'.	Angiv grænsen for. hvad, der tolkes som 'betydelig korrelation'.
170	Missings	Manglende observationer
171	Class	Klasse
172	Observations	Observationer
173	Data classes and missing observations	Dataklasser og manglende observationer
174	Sure you want to reset data? This cannot be undone.	Er du sikker på at du vil gendanne data? Det kan ikke fortrydes.
175	Cancel	Afbryd
176	Confirm	Bekræft
177	The filtered data	Filtreret data
178	Create new factor	Ny kategorisk variabel
179	This window is aimed at advanced users and require some *R*-experience!	This window is aimed at advanced users and require some *R*-experience!
180	Create new variables	Opret ny variabel
181	Select data types to include	Vælg datatyper, der skal inkluderes
182	Uploaded data overview	Overblik over uploaded data
183	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.	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.
184	Specify covariables	Angiv kovariabler
185	If none are selected, all are included.	Hvis ingen er valgt inkluderes alle.
186	Analyse	Analysér
187	Working...	Arbejder...
188	Press 'Analyse' to create the regression model and after changing parameters.	Tryk 'Analysér' for at danne regressionsmodel og for at opdatere hvis parametre ændres.
189	Show p-value	Vis p-værdi
190	Model checks	Model-test
191	Please confirm data reset!	Bekræft gendannelse af data!
192	Import data from REDCap	Importér data fra REDCap
193	REDCap server	REDCap-server
194	Web address	Web address
195	Format should be either 'https://redcap.your.institution/' or 'https://your.institution/redcap/'	Adressen skal være som 'https://redcap.your.institution/' eller 'https://your.institution/redcap/'
196	API token	API token
197	The token is a string of 32 numbers and letters.	En API-nøgle består af ialt 32 tal og bogstaver.
198	Connect	Forbind
199	Data import parameters	Data import parameters
200	Select fields/variables to import and click the funnel to apply optional filters	Select fields/variables to import and click the funnel to apply optional filters
201	Import	Import
202	Click to see data dictionary	Click to see data dictionary
203	Connected to server!	Connected to server!
204	The {data_rv$info$project_title} project is loaded.	The {data_rv$info$project_title} project is loaded.
205	Data dictionary	Data dictionary
206	Preview:	Preview:
207	Imported data set	Imported data set
208	Select fields/variables to import:	Select fields/variables to import:
209	Specify the data format	Specify the data format
210	Fill missing values?	Fill missing values?
211	Requested data was retrieved!	Requested data was retrieved!
212	Data retrieved, but it looks like only the ID was retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.	Data retrieved, but it looks like only the ID was retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.
213	Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.	Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.
214	Click to see the imported data	Click to see the imported data
215	Regression table	Regression table
216	Import a dataset from an environment	Import a dataset from an environment
217	Select a dataset:	Vælg datasæt:
218	List of datasets...	List of datasets...
219	No data selected!	Ingen data valgt!
220	Use a datasat from your environment or from the environment of a package.	Use a datasat from your environment or from the environment of a package.
221	No dataset here...	Ingen datasæt her...
222	Use a dataset from your environment or from the environment of a package.	Use a dataset from your environment or from the environment of a package.
223	Not a data.frame	Ikke en data.frame
224	Select source	Vælg datakilde
225	Select a data source:	Vælg datakilde:
226	Yes	Ja
227	No	Nej
228	Coefficient plot	Coefficient plot
229	Select outcome variable	Select outcome variable
230	Choose regression analysis	Choose regression analysis
231	Covariables to format as categorical	Covariables to format as categorical
232	Select variable to stratify baseline	Select variable to stratify baseline
233	Select models to plot	Select models to plot
234	Creating regression models failed with the following error:	Creating regression models failed with the following error:
235	Creating a regression table failed with the following error:	Creating a regression table failed with the following error:
236	Saving the plot. Hold on for a moment..	Saving the plot. Hold on for a moment..
237	Running model assumptions checks failed with the following error:	Running model assumptions checks failed with the following error:
238	Select checks to plot	Select checks to plot
239	Multivariable regression model checks	Multivariable regression model checks
240	Grouped by {get_label(data,ter)}	Grouped by {get_label(data,ter)}
241	Option to perform statistical comparisons between strata in baseline table.	Option to perform statistical comparisons between strata in baseline table.
242	Press 'Evaluate' to create the comparison table.	Press 'Evaluate' to create the comparison table.
243	The data includes {n_col} variables. Please limit to 100.	The data includes {n_col} variables. Please limit to 100.
244	Data import	Data import
245	Data import formatting	Data import formatting
246	Data modifications	Data modifications
247	Variables filter	Variables filter
248	Data filter	Data filter
249	Data characteristics table	Data characteristics table
250	The dataset without text variables	The dataset without text variables
251	Creating the table. Hold on for a moment..	Creating the table. Hold on for a moment..
252	Select variable to stratify analysis	Select variable to stratify analysis
253	Generating the report. Hold on for a moment..	Generating the report. Hold on for a moment..
254	We encountered the following error showing missingness:	We encountered the following error showing missingness:
255	We encountered the following error browsing your data:	We encountered the following error browsing your data:
256	To consider if data is missing by random, choose the outcome/dependent variable (only variables with any missings are available). If there is a significant difference across other variables depending on missing observations, it may not be missing at random.	To consider if data is missing by random, choose the outcome/dependent variable (only variables with any missings are available). If there is a significant difference across other variables depending on missing observations, it may not be missing at random.
257	Choose a name for the column to be created or modified, then enter an expression before clicking on the button below to create the variable, or cancel to exit without saving anything.	Choose a name for the column to be created or modified, then enter an expression before clicking on the button below to create the variable, or cancel to exit without saving anything.