FreesearchR/app_docker/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	A classical way of visualising the distribution of an ordinal scale like the modified Ranking Scale and known as Grotta bars
133	Violin plot	Violin plot
134	A modern alternative to the classic boxplot to visualise data distribution	A modern alternative to the classic boxplot to visualise data distribution
135	Sankey plot	Sankey plot
136	A way of visualising change between groups	A way of visualising change between groups
137	Scatter plot	Scatter plot
138	A classic way of showing the association between to variables	A classic way of showing the association between to variables
139	Box plot	Box plot
140	A classic way to plot data distribution by groups	A classic way to plot data distribution by groups
141	Euler diagram	Eulerdiagram
142	Generate area-proportional Euler diagrams to display set relationships	Generate area-proportional Euler diagrams to display set relationships
143	Documentation	Dokumentation
144	Data is only stored for analyses and deleted when the app is closed.	Data is only stored for analyses and deleted when the app is closed.
145	Consider [running ***FreesearchR*** locally](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine) if working with sensitive data.	Consider [running ***FreesearchR*** locally](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine) if working with sensitive 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	Checks
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.	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.
154	Browse observations	Gennemse observationer
155	Settings	Indstillinger
156	The following error occured on determining correlations:	The following error occured on determining correlations:
157	We encountered the following error creating your report:	We encountered the following error creating your report:
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}.	There is a significant correlation between {n_nonmcar} variables and missing observations in the outcome variable {outcome}.
162	There is a total of {p_miss} % missing observations.	Der er i alt {p_miss} % manglende observationer.