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	Choose a name for the column to be created or modified,	Vælg et navn til den ændrede eller nye variabel,
48	then enter an expression before clicking on the button above to validate or on	indtast herefter udregningen før du trykker på knappen ovenfor for at validere eller på
49	to delete it.	for at slette den.
50	New column name cannot be empty	Det nye variabelnavn kan ikke være tomt
51	Create a new column	Opret ny variabel
52	Some operations are not allowed	Nogle beregninger er ikke tilladte
53	Column added!	Variabel oprettet!
54	Unique values:	Unikke værdier:
55	Variable to cut:	Variabel, der skal deles:
56	Number of breaks:	Antal niveauer:
57	Close intervals on the right	Luk intervaller til højre
58	Include lowest value	Inkluderer den laveste værdi
59	Create factor variable	Opret kategorisk variabel
60	Fixed breaks:	Faste niveauer:
61	Method:	Metode:
62	Convert Numeric to Factor	Konverter numerisk til kategorisk
63	Unique:	Unique:
64	Missing:	Manglende:
65	Most Common:	Mest hyppige:
66	Min:	Min:
67	Mean:	Mean:
68	Max:	Max:
69	Decimal separator:	Decimal adskiller:
70	First five rows are shown below:	De første fem rækker vises nedenfor:
71	Imported data	Importeret data
72	www/intro.md	www/intro.md
73	Choose your data	Vælg dine data
74	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.
75	Factor variable to reorder:	Kategoriske variabel der skal ændres:
76	Sort by levels	Sorter efter niveauer
77	Sort by count	Sorter efter antal
78	Create a new variable (otherwise replaces the one selected)	Opret en ny variabel (ellers erstattes den oprindelige)
79	Update factor variable	Updater faktor-variabel
80	Sort count	Sorter antal
81	Levels	Niveauer
82	Count	Antal
83	Update levels of a factor	Updater niveauerne for en faktor
84	Update & select variables	Opdater og vælg variabler
85	Date format:	Datoformat:
86	Date to use as origin to convert date/datetime:	Dato, der skal anvendes som udgangspunkt for konvertering af dato/datotid:
87	Apply changes	Anvend ændringer
88	No data to display.	Ingen data at vise.
89	Data successfully updated!	Data er opdateret!
90	You removed {p_out} % of observations.	Du har fjernet {p_out} % af observationerne.
91	You removed {p_out} % of variables.	Du har fjernet {p_out} % af variablerne.
92	You can import {file_extensions_text} files	Du kan vælge mellem disse filtyper: {file_extensions_text}
93	You can choose between these file types:	Du kan vælge mellem følgene filtyper:
94	Rows to skip before reading data:	Rækker der skal springes over:
95	Missing values character(s):	Tegn for manglende værdier:
96	if several use a comma (',') to separate them	hvis flere, så anvend et komma (',') som seperator
97	Encoding:	Kodning:
98	Upload a file:	Upload en fil:
99	Browse...	Vælg...
100	Select sheet to import:	Vælg ark:
101	No file selected.	Ingen fil valgt.
102	Evaluate	Evaluer
103	Visuals	Grafik
104	Regression	Regression
105	Download	Download
106	{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.
107	Prepare	Forbered
108	At 0, only complete variables are included; at 100, all variables are included.	Ved 0 inkluderes alene komplette variabler; ved 100 inkluderes alle variabler.
109	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.
110	No variables have a correlation measure above the threshold.	Ingen variabler er korrelerede over den angivne tærskelværdi.
111	and	og
112	from each pair	fra hvert par
113	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.
114	Plot	Tegn
115	Adjust settings, then press "Plot".	Juster indstillingerne og tryk så "Tegn".
116	Plot height (mm)	Højde af grafik (mm)
117	Plot width (mm)	Bredde af grafik (mm)
118	File format	File format
119	Download plot	Download grafik
120	Select variable	Vælg variabel
121	Response variable	Svarvariable
122	Plot type	Type af grafik
123	Please select	Vælg
124	Additional variables	Yderligere variabler
125	Secondary variable	Sekundær variabel
126	No variable	Ingen variabel
127	Grouping variable	Variabel til gruppering
128	No stratification	Ingen stratificering
129	Drawing the plot. Hold tight for a moment..	Tegner grafikken. Spænd selen..
130	#Plotting\n	#Tegner\n
131	Stacked horizontal bars	Stablede horisontale søjler
132	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'
133	Violin plot	Violin-diagram
134	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
135	Sankey plot	Sankey-diagram
136	A way of visualising change between groups	Visualiserer ændring mellem grupper for samme type observationer
137	Scatter plot	Punkt-diagram
138	A classic way of showing the association between to variables	Visualiserer forholdet mellem to variabler
139	Box plot	Kasse-diagram
140	A classic way to plot data distribution by groups	Klassik måde at visualisere fordeling
141	Euler diagram	Eulerdiagram
142	Generate area-proportional Euler diagrams to display set relationships	Generer proportionelt Euler-diagram for at vise forhold mellem forskellige kategoriske observationer
143	Documentation	Dokumentation
144	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.
145	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.
146	Feedback	Feedback
147	License: AGPLv3	Licens: AGPLv3
148	Source	Kilde
149	Data includes {n_pairs} pairs of highly correlated variables.	Der er {n_pairs} variabel-par, der er stærkt internt korrelerede.
150	Create plot	Dan grafik
151	Coefficients plot	Koefficientgraf
152	Checks	Test af model
153	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.
154	Browse observations	Gennemse observationer
155	Settings	Indstillinger
156	The following error occured on determining correlations:	Følgende fejl opstod i forbindelse med korrelationsanalysen:
157	We encountered the following error creating your report:	Følgende fejl opstod, da rapporten blev dannet:
158	No variable chosen for analysis	Ingen variabel er valgt til analysen
159	No missing observations	Ingen manglende observationer
160	Missing vs non-missing observations in the variable **'{variabler()}'**	Manglende vs ikke-manglende observationer i variablen **'{variabler()}'**
161	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}.
162	There is a total of {p_miss} % missing observations.	Der er i alt {p_miss} % manglende observationer.
163	Median:	Median:
164	Restore original data	Gendan originale data
165	Reset to original imported dataset. Careful! There is no un-doing.	Gendan det oprindeligt importerede datasæt. Forsigtig! Alle dine ændringer vil forsvinde.
166	Characteristics	Karakteristika
167	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.
168	Compare strata?	Sammenlign strata?
169	Correlations	Korrelationer
170	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.
171	Correlation cut-off	Korrelationsgrænse
172	Set the cut-off for considered 'highly correlated'.	Angiv grænsen for. hvad, der tolkes som 'betydelig korrelation'.
173	Missings	Manglende observationer
174	To consider if data is missing by random, choose the outcome/dependent variable, if it has any missings to evaluate if there is a significant difference across other variables depending on missing data or not.	To consider if data is missing by random, choose the outcome/dependent variable, if it has any missings to evaluate if there is a significant difference across other variables depending on missing data or not.
175	Class	Klasse
176	Observations	Observationer
177	Data classes and missing observations	Dataklasser og manglende observationer
178	Sure you want to reset data? This cannot be undone.	Er du sikker på at du vil gendanne data? Det kan ikke fortrydes.
179	Cancel	Afbryd
180	Confirm	Bekræft
181	The filtered data	Filtreret data
182	Create new factor	Ny kategorisk variabel
183	This window is aimed at advanced users and require some *R*-experience!	This window is aimed at advanced users and require some *R*-experience!
184	Create new variables	Opret ny variabel
185	Select data types to include	Vælg datatyper, der skal inkluderes
186	Uploaded data overview	Overblik over uploaded data
187	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.
188	#Data import\n	#Data import\n
189	#Data import formatting\n	#Formatering ved data-import\n
190	Specify covariables	Angiv kovariabler
191	If none are selected, all are included.	Hvis ingen er valgt inkluderes alle.
192	Analyse	Analysér
193	Working...	Arbejder...
194	Press 'Analyse' to create the regression model and after changing parameters.	Tryk 'Analysér' for at danne regressionsmodel og for at opdatere hvis parametre ændres.
195	Show p-value	Vis p-værdi
196	Model checks	Model-test
197	Please confirm data reset!	Bekræft gendannelse af data!
198	Import data from REDCap	Importér data fra REDCap
199	REDCap server	REDCap-server
200	Web address	Web address
201	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/'
202	API token	API token
203	The token is a string of 32 numbers and letters.	En API-nøgle består af ialt 32 tal og bogstaver.
204	Connect	Forbind
205	Data import parameters	Data import parameters
206	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
207	Import	Import
208	Click to see data dictionary	Click to see data dictionary
209	Connected to server!	Connected to server!
210	The {data_rv$info$project_title} project is loaded.	The {data_rv$info$project_title} project is loaded.
211	Data dictionary	Data dictionary
212	Preview:	Preview:
213	Imported data set	Imported data set
214	Select fields/variables to import:	Select fields/variables to import:
215	Specify the data format	Specify the data format
216	Fill missing values?	Fill missing values?
217	Requested data was retrieved!	Requested data was retrieved!
218	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.
219	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.
220	Click to see the imported data	Click to see the imported data
221	Regression table	Regression table
222	Import a dataset from an environment	Import a dataset from an environment
223	Select a dataset:	Vælg datasæt:
224	List of datasets...	List of datasets...
225	No data selected!	Ingen data valgt!
226	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.
227	No dataset here...	Ingen datasæt her...
228	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.
229	Not a data.frame	Ikke en data.frame
230	Select source	Vælg datakilde
231	Select a data source:	Vælg datakilde:
232	Yes	Ja
233	No	Nej
234	Coefficient plot	Coefficient plot
235	Select outcome variable	Select outcome variable
236	Choose regression analysis	Choose regression analysis
237	Covariables to format as categorical	Covariables to format as categorical
238	Select variable to stratify baseline	Select variable to stratify baseline
239	Select models to plot	Select models to plot
240	Creating regression models failed with the following error:	Creating regression models failed with the following error:
241	Creating a regression table failed with the following error:	Creating a regression table failed with the following error:
242	Saving the plot. Hold on for a moment..	Saving the plot. Hold on for a moment..
243	Running model assumptions checks failed with the following error:	Running model assumptions checks failed with the following error:
244	Select checks to plot	Select checks to plot
245	Multivariable regression model checks	Multivariable regression model checks
246	Grouped by {get_label(data,ter)}	Grouped by {get_label(data,ter)}
247	Option to perform statistical comparisons between strata in baseline table.	Option to perform statistical comparisons between strata in baseline table.
248	Press 'Evaluate' to create the comparison table.	Press 'Evaluate' to create the comparison table.
249	The data includes {n_col} variables. Please limit to 100.	The data includes {n_col} variables. Please limit to 100.