FreesearchR/inst/translations/translation_sv.csv

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