FreesearchR/app_docker/translations/translation_de.csv

1	en	de
2	Hello	Hallo
3	The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.	The following variable pairs are highly correlated: {sentence_paste(.x,and_str)}.\nConsider excluding one {more}from the dataset to ensure variables are independent.
4	No variables have a correlation measure above the threshold.	No variables have a correlation measure above the threshold.
5	and	and
6	The following error occured on determining correlations:	The following error occured on determining correlations:
7	from each pair	from each pair
8	New column name:	New column name:
9	Group calculation by:	Group calculation by:
10	Enter an expression to define new column:	Enter an expression to define new column:
11	Click on a column name to add it to the expression:	Click on a column name to add it to the expression:
12	Create column	Create column
13	Cancel	Cancel
14	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.
15	New column name cannot be empty	New column name cannot be empty
16	Create a new column	Create a new column
17	Some operations are not allowed	Some operations are not allowed
18	Column added!	Column added!
19	Unique values:	Unique values:
20	Variable to cut:	Variable to cut:
21	Number of breaks:	Number of breaks:
22	Close intervals on the right	Close intervals on the right
23	Include lowest value	Include lowest value
24	Create factor variable	Create factor variable
25	Fixed breaks:	Fixed breaks:
26	Method:	Method:
27	Other	Other
28	Convert Numeric to Factor	Convert Numeric to Factor
29	Hour of the day	Hour of the day
30	Breaks	Breaks
31	By day of the week	By day of the week
32	By weekday	By weekday
33	By week number and year	By week number and year
34	By week number	By week number
35	By month and year	By month and year
36	By month only	By month only
37	By quarter of the year	By quarter of the year
38	By year	By year
39	Keep only most common	Keep only most common
40	Number	Number
41	Combine below percentage	Combine below percentage
42	Percentage	Percentage
43	By specified numbers	By specified numbers
44	By quantiles (groups of equal size)	By quantiles (groups of equal size)
45	Only non-text variables are available for plotting. Go the "Data" to reclass data to plot.	Only non-text variables are available for plotting. Go the "Data" to reclass data to plot.
46	Plot	Plot
47	Adjust settings, then press "Plot".	Adjust settings, then press "Plot".
48	Plot height (mm)	Plot height (mm)
49	Plot width (mm)	Plot width (mm)
50	File format	File format
51	Download plot	Download plot
52	Create plot	Create plot
53	Download	Download
54	Select variable	Select variable
55	Response variable	Response variable
56	Plot type	Plot type
57	Please select	Please select
58	Additional variables	Additional variables
59	Secondary variable	Secondary variable
60	No variable	No variable
61	Grouping variable	Grouping variable
62	No stratification	No stratification
63	Drawing the plot. Hold tight for a moment..	Drawing the plot. Hold tight for a moment..
64	#Plotting\n	#Plotting\n
65	Stacked horizontal bars	Stacked horizontal bars
66	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
67	Violin plot	Violin plot
68	A modern alternative to the classic boxplot to visualise data distribution	A modern alternative to the classic boxplot to visualise data distribution
69	Sankey plot	Sankey plot
70	A way of visualising change between groups	A way of visualising change between groups
71	Scatter plot	Scatter plot
72	A classic way of showing the association between to variables	A classic way of showing the association between to variables
73	Box plot	Box plot
74	A classic way to plot data distribution by groups	A classic way to plot data distribution by groups
75	Euler diagram	Euler diagram
76	Generate area-proportional Euler diagrams to display set relationships	Generate area-proportional Euler diagrams to display set relationships
77	Unique:	Unique:
78	Missing:	Missing:
79	Most Common:	Most Common:
80	Min:	Min:
81	Mean:	Mean:
82	Median:	Median:
83	Max:	Max:
84	{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.	{data_text} has {n} observations and {n_var} variables, with {n_complete} ({p_complete} %) complete cases.
85	Import a dataset from an environment	Import a dataset from an environment
86	Select a data source:	Select a data source:
87	Select source	Select source
88	Select a dataset:	Select a dataset:
89	List of datasets...	List of datasets...
90	No data selected!	No data selected!
91	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.
92	No dataset here...	No dataset here...
93	Imported data	Imported data
94	Not a data.frame	Not a data.frame
95	Rows to skip before reading data:	Rows to skip before reading data:
96	Missing values character(s):	Missing values character(s):
97	if several use a comma (',') to separate them	if several use a comma (',') to separate them
98	Decimal separator:	Decimal separator:
99	Encoding:	Encoding:
100	Upload a file:	Upload a file:
101	Browse...	Browse...
102	Select sheet to import:	Select sheet to import:
103	No file selected.	No file selected.
104	You can choose between these file types:	You can choose between these file types:
105	You can import {file_extensions_text} files	You can import {file_extensions_text} files
106	First five rows are shown below:	First five rows are shown below:
107	No variable chosen for analysis	No variable chosen for analysis
108	No missing observations	No missing observations
109	Missing vs non-missing observations in the variable **'{variabler()}'**	Missing vs non-missing observations in the variable **'{variabler()}'**
110	Grouped by {get_label(data,ter)}	Grouped by {get_label(data,ter)}
111	Import data from REDCap	Import data from REDCap
112	REDCap server	REDCap server
113	Web address	Web address
114	Format should be either 'https://redcap.your.institution/' or 'https://your.institution/redcap/'	Format should be either 'https://redcap.your.institution/' or 'https://your.institution/redcap/'
115	API token	API token
116	The token is a string of 32 numbers and letters.	The token is a string of 32 numbers and letters.
117	Connect	Connect
118	Please fill in web address and API token, then press 'Connect'.	Please fill in web address and API token, then press 'Connect'.
119	Data import parameters	Data import parameters
120	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
121	Import	Import
122	Click to see data dictionary	Click to see data dictionary
123	Connected to server!	Connected to server!
124	The {data_rv$info$project_title} project is loaded.	The {data_rv$info$project_title} project is loaded.
125	Data dictionary	Data dictionary
126	Preview:	Preview:
127	Imported data set	Imported data set
128	Select fields/variables to import:	Select fields/variables to import:
129	Specify the data format	Specify the data format
130	Fill missing values?	Fill missing values?
131	Requested data was retrieved!	Requested data was retrieved!
132	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.
133	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.
134	Click to see the imported data	Click to see the imported data
135	Regression table	Regression table
136	Regression	Regression
137	Specify covariables	Specify covariables
138	If none are selected, all are included.	If none are selected, all are included.
139	Analyse	Analyse
140	Working...	Working...
141	Press 'Analyse' to create the regression model and after changing parameters.	Press 'Analyse' to create the regression model and after changing parameters.
142	Coefficient plot	Coefficient plot
143	Model checks	Model checks
144	Coefficients plot	Coefficients plot
145	Checks	Checks
146	Yes	Yes
147	No	No
148	Show p-value	Show p-value
149	Select outcome variable	Select outcome variable
150	Choose regression analysis	Choose regression analysis
151	Covariables to format as categorical	Covariables to format as categorical
152	Select variable to stratify baseline	Select variable to stratify baseline
153	Select models to plot	Select models to plot
154	Creating regression models failed with the following error:	Creating regression models failed with the following error:
155	Creating a regression table failed with the following error:	Creating a regression table failed with the following error:
156	Saving the plot. Hold on for a moment..	Saving the plot. Hold on for a moment..
157	Running model assumptions checks failed with the following error:	Running model assumptions checks failed with the following error:
158	Select checks to plot	Select checks to plot
159	Multivariable regression model checks	Multivariable regression model checks
160	www/intro.html	www/intro.html
161	www/intro.md	www/intro.md
162	Get started	Get started
163	Choose your data	Choose your data
164	Upload a file, get data directly from REDCap or use local or sample data.	Upload a file, get data directly from REDCap or use local or sample data.
165	Please be mindfull handling sensitive data	Please be mindfull handling sensitive data
166	<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>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>
167	Quick overview	Quick overview
168	Select variables for final import	Select variables for final import
169	Exclude incomplete variables:	Exclude incomplete variables:
170	At 0, only complete variables are included; at 100, all variables are included.	At 0, only complete variables are included; at 100, all variables are included.
171	Manual selection:	Manual selection:
172	Let's begin!	Let's begin!
173	Prepare	Prepare
174	Overview and filter	Overview and filter
175	Overview and filtering	Overview and filtering
176	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.
177	Visual overview	Visual overview
178	Browse observations	Browse observations
179	Filter data types	Filter data types
180	Filter observations	Filter observations
181	Apply filter on observation	Apply filter on observation
182	Edit and create data	Edit and create data
183	Subset, rename and convert variables	Subset, rename and convert variables
184	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.).	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.).
185	Please note that data modifications are applied before any filtering.	Please note that data modifications are applied before any filtering.
186	Advanced data manipulation	Advanced data manipulation
187	Below options allow more advanced varaible manipulations.	Below options allow more advanced varaible manipulations.
188	Reorder factor levels	Reorder factor levels
189	Reorder the levels of factor/categorical variables.	Reorder the levels of factor/categorical variables.
190	New factor	New factor
191	Create factor/categorical variable from a continous variable (number/date/time).	Create factor/categorical variable from a continous variable (number/date/time).
192	New variable	New variable
193	Create a new variable based on an R-expression.	Create a new variable based on an R-expression.
194	Compare modified data to original	Compare modified data to original
195	Raw print of the original vs the modified data.	Raw print of the original vs the modified data.
196	Original data:	Original data:
197	Modified data:	Modified data:
198	Restore original data	Restore original data
199	Reset to original imported dataset. Careful! There is no un-doing.	Reset to original imported dataset. Careful! There is no un-doing.
200	Evaluate	Evaluate
201	Characteristics	Characteristics
202	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.	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.
203	Compare strata?	Compare strata?
204	Option to perform statistical comparisons between strata in baseline table.	Option to perform statistical comparisons between strata in baseline table.
205	Press 'Evaluate' to create the comparison table.	Press 'Evaluate' to create the comparison table.
206	Correlations	Correlations
207	To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.	To avoid evaluating the correlation of the outcome variable, this can be excluded from the plot or select 'none'.
208	Correlation cut-off	Correlation cut-off
209	Set the cut-off for considered 'highly correlated'.	Set the cut-off for considered 'highly correlated'.
210	Missings	Missings
211	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.
212	Visuals	Visuals
213	Analysis validation	Analysis validation
214	Report	Report
215	Choose your favourite output file format for further work, and download, when the analyses are done.	Choose your favourite output file format for further work, and download, when the analyses are done.
216	Factor variable to reorder:	Factor variable to reorder:
217	Sort by levels	Sort by levels
218	Sort by count	Sort by count
219	Create a new variable (otherwise replaces the one selected)	Create a new variable (otherwise replaces the one selected)
220	Update factor variable	Update factor variable
221	Sort count	Sort count
222	Levels	Levels
223	Count	Count
224	Update levels of a factor	Update levels of a factor
225	Update & select variables	Update & select variables
226	Date format:	Date format:
227	Date to use as origin to convert date/datetime:	Date to use as origin to convert date/datetime:
228	Apply changes	Apply changes
229	No data to display.	No data to display.
230	Data successfully updated!	Data successfully updated!
231	You removed {p_out} % of observations.	You removed {p_out} % of observations.
232	You removed {p_out} % of variables.	You removed {p_out} % of variables.
233	There is a total of {p_miss} % missing observations.	There is a total of {p_miss} % missing observations.
234	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}.
235	Data includes {n_pairs} pairs of highly correlated variables.	Data includes {n_pairs} pairs of highly correlated variables.
236	Class	Class
237	Observations	Observations
238	File upload	File upload
239	REDCap server export	REDCap server export
240	Local or sample data	Local or sample data
241	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.
242	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.
243	Documentation	Documentation
244	Feedback	Feedback
245	License: AGPLv3	License: AGPLv3
246	Source	Source
247	Settings	Settings
248	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).	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).
249	Data classes and missing observations	Data classes and missing observations
250	We encountered the following error showing missingness:	We encountered the following error showing missingness:
251	Please confirm data reset!	Please confirm data reset!
252	Sure you want to reset data? This cannot be undone.	Sure you want to reset data? This cannot be undone.
253	Confirm	Confirm
254	The filtered data	The filtered data
255	Create new factor	Create new factor
256	This window is aimed at advanced users and require some *R*-experience!	This window is aimed at advanced users and require some *R*-experience!
257	Create new variables	Create new variables
258	Select data types to include	Select data types to include
259	Uploaded data overview	Uploaded data overview
260	We encountered the following error browsing your data:	We encountered the following error browsing your data:
261	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.
262	Data import	Data import
263	Data import formatting	Data import formatting
264	Data modifications	Data modifications
265	Variables filter	Variables filter
266	Data filter	Data filter
267	Data characteristics table	Data characteristics table
268	The dataset without text variables	The dataset without text variables
269	The data includes {n_col} variables. Please limit to 100.	The data includes {n_col} variables. Please limit to 100.
270	Creating the table. Hold on for a moment..	Creating the table. Hold on for a moment..
271	Select variable to stratify analysis	Select variable to stratify analysis
272	Generating the report. Hold on for a moment..	Generating the report. Hold on for a moment..
273	We encountered the following error creating your report:	We encountered the following error creating your report:
274	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.	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.