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	Grouped by {get_label(data,ter)}	Grouped by {get_label(data,ter)}
109	Import data from REDCap	Import data from REDCap
110	REDCap server	REDCap server
111	Web address	Web address
112	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/'
113	API token	API token
114	The token is a string of 32 numbers and letters.	The token is a string of 32 numbers and letters.
115	Connect	Connect
116	Please fill in web address and API token, then press 'Connect'.	Please fill in web address and API token, then press 'Connect'.
117	Data import parameters	Data import parameters
118	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
119	Import	Import
120	Click to see data dictionary	Click to see data dictionary
121	Connected to server!	Connected to server!
122	The {data_rv$info$project_title} project is loaded.	The {data_rv$info$project_title} project is loaded.
123	Data dictionary	Data dictionary
124	Preview:	Preview:
125	Imported data set	Imported data set
126	Select fields/variables to import:	Select fields/variables to import:
127	Specify the data format	Specify the data format
128	Fill missing values?	Fill missing values?
129	Requested data was retrieved!	Requested data was retrieved!
130	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.
131	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.
132	Click to see the imported data	Click to see the imported data
133	Regression table	Regression table
134	Regression	Regression
135	Specify covariables	Specify covariables
136	If none are selected, all are included.	If none are selected, all are included.
137	Analyse	Analyse
138	Working...	Working...
139	Press 'Analyse' to create the regression model and after changing parameters.	Press 'Analyse' to create the regression model and after changing parameters.
140	Coefficient plot	Coefficient plot
141	Model checks	Model checks
142	Coefficients plot	Coefficients plot
143	Checks	Checks
144	Yes	Yes
145	No	No
146	Show p-value	Show p-value
147	Select outcome variable	Select outcome variable
148	Choose regression analysis	Choose regression analysis
149	Covariables to format as categorical	Covariables to format as categorical
150	Select variable to stratify baseline	Select variable to stratify baseline
151	Select models to plot	Select models to plot
152	Creating regression models failed with the following error:	Creating regression models failed with the following error:
153	Creating a regression table failed with the following error:	Creating a regression table failed with the following error:
154	Saving the plot. Hold on for a moment..	Saving the plot. Hold on for a moment..
155	Running model assumptions checks failed with the following error:	Running model assumptions checks failed with the following error:
156	Select checks to plot	Select checks to plot
157	Multivariable regression model checks	Multivariable regression model checks
158	www/intro.html	www/intro.html
159	www/intro.md	www/intro.md
160	Get started	Get started
161	Choose your data	Choose your data
162	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.
163	Please be mindfull handling sensitive data	Please be mindfull handling sensitive data
164	<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>
165	Quick overview	Quick overview
166	Select variables for final import	Select variables for final import
167	Exclude incomplete variables:	Exclude incomplete variables:
168	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.
169	Manual selection:	Manual selection:
170	Let's begin!	Let's begin!
171	Prepare	Prepare
172	Overview and filter	Overview and filter
173	Overview and filtering	Overview and filtering
174	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.
175	Visual overview	Visual overview
176	Browse observations	Browse observations
177	Filter data types	Filter data types
178	Filter observations	Filter observations
179	Apply filter on observation	Apply filter on observation
180	Edit and create data	Edit and create data
181	Subset, rename and convert variables	Subset, rename and convert variables
182	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.).
183	Please note that data modifications are applied before any filtering.	Please note that data modifications are applied before any filtering.
184	Advanced data manipulation	Advanced data manipulation
185	Below options allow more advanced varaible manipulations.	Below options allow more advanced varaible manipulations.
186	Reorder factor levels	Reorder factor levels
187	Reorder the levels of factor/categorical variables.	Reorder the levels of factor/categorical variables.
188	New factor	New factor
189	Create factor/categorical variable from a continous variable (number/date/time).	Create factor/categorical variable from a continous variable (number/date/time).
190	New variable	New variable
191	Create a new variable based on an R-expression.	Create a new variable based on an R-expression.
192	Compare modified data to original	Compare modified data to original
193	Raw print of the original vs the modified data.	Raw print of the original vs the modified data.
194	Original data:	Original data:
195	Modified data:	Modified data:
196	Restore original data	Restore original data
197	Reset to original imported dataset. Careful! There is no un-doing.	Reset to original imported dataset. Careful! There is no un-doing.
198	Evaluate	Evaluate
199	Characteristics	Characteristics
200	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.
201	Compare strata?	Compare strata?
202	Option to perform statistical comparisons between strata in baseline table.	Option to perform statistical comparisons between strata in baseline table.
203	Press 'Evaluate' to create the comparison table.	Press 'Evaluate' to create the comparison table.
204	Correlations	Correlations
205	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'.
206	Correlation cut-off	Correlation cut-off
207	Set the cut-off for considered 'highly correlated'.	Set the cut-off for considered 'highly correlated'.
208	Missings	Missings
209	Visuals	Visuals
210	Analysis validation	Analysis validation
211	Report	Report
212	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.
213	Factor variable to reorder:	Factor variable to reorder:
214	Sort by levels	Sort by levels
215	Sort by count	Sort by count
216	Create a new variable (otherwise replaces the one selected)	Create a new variable (otherwise replaces the one selected)
217	Update factor variable	Update factor variable
218	Sort count	Sort count
219	Levels	Levels
220	Count	Count
221	Update levels of a factor	Update levels of a factor
222	Update & select variables	Update & select variables
223	Date format:	Date format:
224	Date to use as origin to convert date/datetime:	Date to use as origin to convert date/datetime:
225	Apply changes	Apply changes
226	No data to display.	No data to display.
227	Data successfully updated!	Data successfully updated!
228	You removed {p_out} % of observations.	You removed {p_out} % of observations.
229	You removed {p_out} % of variables.	You removed {p_out} % of variables.
230	There is a total of {p_miss} % missing observations.	There is a total of {p_miss} % missing observations.
231	Data includes {n_pairs} pairs of highly correlated variables.	Data includes {n_pairs} pairs of highly correlated variables.
232	Class	Class
233	Observations	Observations
234	File upload	File upload
235	REDCap server export	REDCap server export
236	Local or sample data	Local or sample data
237	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.
238	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.
239	Documentation	Documentation
240	Feedback	Feedback
241	License: AGPLv3	License: AGPLv3
242	Source	Source
243	Settings	Settings
244	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).
245	Data classes and missing observations	Data classes and missing observations
246	We encountered the following error showing missingness:	We encountered the following error showing missingness:
247	Please confirm data reset!	Please confirm data reset!
248	Sure you want to reset data? This cannot be undone.	Sure you want to reset data? This cannot be undone.
249	Confirm	Confirm
250	The filtered data	The filtered data
251	Create new factor	Create new factor
252	This window is aimed at advanced users and require some *R*-experience!	This window is aimed at advanced users and require some *R*-experience!
253	Create new variables	Create new variables
254	Select data types to include	Select data types to include
255	Uploaded data overview	Uploaded data overview
256	We encountered the following error browsing your data:	We encountered the following error browsing your data:
257	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.
258	Data import	Data import
259	Data import formatting	Data import formatting
260	Data modifications	Data modifications
261	Variables filter	Variables filter
262	Data filter	Data filter
263	Data characteristics table	Data characteristics table
264	The dataset without text variables	The dataset without text variables
265	The data includes {n_col} variables. Please limit to 100.	The data includes {n_col} variables. Please limit to 100.
266	Creating the table. Hold on for a moment..	Creating the table. Hold on for a moment..
267	Select variable to stratify analysis	Select variable to stratify analysis
268	Generating the report. Hold on for a moment..	Generating the report. Hold on for a moment..
269	We encountered the following error creating your report:	We encountered the following error creating your report:
270	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.
271	Text or character to split string by	Text or character to split string by
272	Split the variable	Split the variable
273	Variable to split:	Variable to split:
274	Direction:	Direction:
275	Split string to multiple columns. Keep number of rows.	Split string to multiple columns. Keep number of rows.
276	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
277	Split character string	Split character string
278	Split text	Split text
279	Split a character string by a common delimiter	Split a character string by a common delimiter
280	Select delimiter	Select delimiter
281	Browse data preview	Browse data preview
282	Original data	Original data
283	Preview of result	Preview of result
284	No character variables with accepted delimiters detected.	No character variables with accepted delimiters detected.
285	Split a text column by a recognised delimiter.	Split a text column by a recognised delimiter.
286	Apply split	Apply split
287	Stacked relative barplot	Stacked relative barplot
288	Create relative stacked barplots to show the distribution of categorical levels	Create relative stacked barplots to show the distribution of categorical levels
289	Side-by-side barplot	Side-by-side barplot
290	Create side-by-side barplot to show the distribution of categorical levels	Create side-by-side barplot to show the distribution of categorical levels
291	Select table theme	Select table theme
292	Level of detail	Level of detail
293	Minimal	Minimal
294	Extensive	Extensive
295	Letters	Letters
296	Words	Words
297	Shorten to first letters	Shorten to first letters
298	Shorten to first words	Shorten to first words
299	Select missings analysis to apply	Select missings analysis to apply
300	Variables	Variables
301	By outcome	By outcome
302	Missings across variables by the variable **'{input$missings_var}'**	Missings across variables by the variable **'{input$missings_var}'**
303	Missing vs non-missing observations in the variable **'{input$missings_var}'**	Missing vs non-missing observations in the variable **'{input$missings_var}'**
304	Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random.	Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random.
305	Calculating. Hold tight for a moment..	Calculating. Hold tight for a moment..
306	There is a significant difference in data missingness in {n_nonmcar} {ifelse(n_nnonmcar==1,'variable','variables')} grouped by the selected outcome/grouping variable {outcome}.	There is a significant difference in data missingness in {n_nonmcar} {ifelse(n_nnonmcar==1,'variable','variables')} grouped by the selected outcome/grouping variable {outcome}.