FreesearchR/inst/translations/translation_sw.csv

1	en	sw
2	Hello	Habari
3	Get started	Tuanze
4	File upload	Upakiaji wa faili
5	REDCap server export	Uhamishaji wa seva ya REDCap
6	Local or sample data	Taarifa za ndani au za mfano
7	Please be mindfull handling sensitive data	Tafadhali kumbuka kushughulikia data nyeti
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).	Programu ya ***FreesearchR*** huhifadhi data kwa uchanganuzi pekee, lakini tafadhali tumia tu na data nyeti unapoendesha ndani ya nchi. [Soma zaidi hapa](https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine).
9	Quick overview	Muhtasari wa haraka
10	Select variables for final import	Chagua vigeu kwa ajili ya uingizaji wa mwisho
11	Exclude incomplete variables:	Usijumuishe vigeu visivyokamilika:
12	Manual selection:	Uchaguzi wa mikono:
13	Let's begin!	Tuanze!
14	Analysis validation	Uthibitishaji wa uchambuzi
15	Report	Ripoti
16	Choose your favourite output file format for further work, and download, when the analyses are done.	Chagua umbizo la faili la towe lako kwa kazi zaidi, na upakue, uchanganuzi utakapofanywa.
17	www/intro.html	www/intro_sw.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>Programu ya <em><strong>FreesearchR</strong></em> huhifadhi data kwa ajili ya uchanganuzi pekee, lakini tafadhali tumia tu na data nyeti unapoendesha ndani ya nchi. <a href='https://agdamsbo.github.io/FreesearchR/#run-locally-on-your-own-machine'>Soma zaidi hapa</a></p>
19	Overview and filter	Muhtasari na chujio
20	Overview and filtering	Muhtasari na uchujaji
21	Visual overview	Muhtasari wa kuona
22	Filter data types	Chuja aina za data
23	Filter observations	Chuja uchunguzi
24	Apply filter on observation	Tumia kichujio unapotazama
25	Edit and create data	Edit and create data
26	Subset, rename and convert variables	Subset, rename and convert variables
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.).	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.).
28	Please note that data modifications are applied before any filtering.	Please note that data modifications are applied before any filtering.
29	Advanced data manipulation	Advanced data manipulation
30	Below options allow more advanced varaible manipulations.	Below options allow more advanced varaible manipulations.
31	Reorder factor levels	Reorder factor levels
32	Reorder the levels of factor/categorical variables.	Reorder the levels of factor/categorical variables.
33	New factor	New factor
34	Create factor/categorical variable from a continous variable (number/date/time).	Create factor/categorical variable from a continous variable (number/date/time).
35	New variable	New variable
36	Create a new variable based on an R-expression.	Create a new variable based on an R-expression.
37	Compare modified data to original	Compare modified data to original
38	Raw print of the original vs the modified data.	Raw print of the original vs the modified data.
39	Original data:	Data asili:
40	Modified data:	Data iliyobadilishwa:
41	New column name:	New column name:
42	Group calculation by:	Group calculation by:
43	Enter an expression to define new column:	Enter an expression to define new column:
44	Click on a column name to add it to the expression:	Click on a column name to add it to the expression:
45	Create column	Create column
46	New column name cannot be empty	New column name cannot be empty
47	Create a new column	Create a new column
48	Some operations are not allowed	Some operations are not allowed
49	Column added!	Column added!
50	Unique values:	Unique values:
51	Variable to cut:	Variable to cut:
52	Close intervals on the right	Close intervals on the right
53	Include lowest value	Include lowest value
54	Create factor variable	Create factor variable
55	Fixed breaks:	Fixed breaks:
56	Method:	Method:
57	Convert Numeric to Factor	Convert Numeric to Factor
58	Unique:	Unique:
59	Missing:	Missing:
60	Most Common:	Most Common:
61	Min:	Min:
62	Mean:	Mean:
63	Max:	Max:
64	Decimal separator:	Decimal separator:
65	First five rows are shown below:	First five rows are shown below:
66	Imported data	Imported data
67	www/intro.md	www/intro.md
68	Choose your data	Choose your data
69	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.
70	Factor variable to reorder:	Factor variable to reorder:
71	Sort by levels	Sort by levels
72	Sort by count	Sort by count
73	Create a new variable (otherwise replaces the one selected)	Create a new variable (otherwise replaces the one selected)
74	Update factor variable	Update factor variable
75	Sort count	Sort count
76	Levels	Levels
77	Count	Count
78	Update levels of a factor	Update levels of a factor
79	Update & select variables	Update & select variables
80	Date format:	Date format:
81	Date to use as origin to convert date/datetime:	Date to use as origin to convert date/datetime:
82	Apply changes	Apply changes
83	No data to display.	No data to display.
84	Data successfully updated!	Data successfully updated!
85	You removed {p_out} % of observations.	You removed {p_out} % of observations.
86	You removed {p_out} % of variables.	You removed {p_out} % of variables.
87	You can import {file_extensions_text} files	You can import {file_extensions_text} files
88	You can choose between these file types:	You can choose between these file types:
89	Rows to skip before reading data:	Rows to skip before reading data:
90	Missing values character(s):	Missing values character(s):
91	if several use a comma (',') to separate them	if several use a comma (',') to separate them
92	Encoding:	Encoding:
93	Upload a file:	Upload a file:
94	Browse...	Browse...
95	Select sheet to import:	Select sheet to import:
96	No file selected.	No file selected.
97	Evaluate	Evaluate
98	Visuals	Visuals
99	Regression	Regression
100	Download	Download
101	{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.
102	Prepare	Prepare
103	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.
104	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.
105	No variables have a correlation measure above the threshold.	No variables have a correlation measure above the threshold.
106	and	and
107	from each pair	from each pair
108	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.
109	Plot	Plot
110	Adjust settings, then press "Plot".	Adjust settings, then press "Plot".
111	Plot height (mm)	Plot height (mm)
112	Plot width (mm)	Plot width (mm)
113	File format	File format
114	Download plot	Download plot
115	Select variable	Select variable
116	Response variable	Response variable
117	Plot type	Plot type
118	Please select	Please select
119	Additional variables	Additional variables
120	Secondary variable	Secondary variable
121	No variable	No variable
122	Grouping variable	Grouping variable
123	No stratification	No stratification
124	Drawing the plot. Hold tight for a moment..	Drawing the plot. Hold tight for a moment..
125	#Plotting\n	#Plotting\n
126	Stacked horizontal bars	Stacked horizontal bars
127	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
128	Violin plot	Violin plot
129	A modern alternative to the classic boxplot to visualise data distribution	A modern alternative to the classic boxplot to visualise data distribution
130	Sankey plot	Sankey plot
131	A way of visualising change between groups	A way of visualising change between groups
132	Scatter plot	Scatter plot
133	A classic way of showing the association between to variables	A classic way of showing the association between to variables
134	Box plot	Box plot
135	A classic way to plot data distribution by groups	A classic way to plot data distribution by groups
136	Euler diagram	Euler diagram
137	Generate area-proportional Euler diagrams to display set relationships	Generate area-proportional Euler diagrams to display set relationships
138	Documentation	Documentation
139	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.
140	Feedback	Feedback
141	License: AGPLv3	License: AGPLv3
142	Source	Source
143	Data includes {n_pairs} pairs of highly correlated variables.	Data includes {n_pairs} pairs of highly correlated variables.
144	Create plot	Create plot
145	Coefficients plot	Coefficients plot
146	Checks	Checks
147	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.
148	Browse observations	Browse observations
149	Settings	Settings
150	The following error occured on determining correlations:	The following error occured on determining correlations:
151	We encountered the following error creating your report:	We encountered the following error creating your report:
152	No missing observations	No missing observations
153	There is a total of {p_miss} % missing observations.	There is a total of {p_miss} % missing observations.
154	Median:	Median:
155	Restore original data	Restore original data
156	Reset to original imported dataset. Careful! There is no un-doing.	Reset to original imported dataset. Careful! There is no un-doing.
157	Characteristics	Characteristics
158	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.
159	Compare strata?	Compare strata?
160	Correlations	Correlations
161	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'.
162	Correlation cut-off	Correlation cut-off
163	Set the cut-off for considered 'highly correlated'.	Set the cut-off for considered 'highly correlated'.
164	Missings	Missings
165	Class	Class
166	Observations	Observations
167	Data classes and missing observations	Data classes and missing observations
168	Sure you want to reset data? This cannot be undone.	Sure you want to reset data? This cannot be undone.
169	Cancel	Cancel
170	Confirm	Confirm
171	The filtered data	The filtered data
172	Create new factor	Create new factor
173	This window is aimed at advanced users and require some *R*-experience!	This window is aimed at advanced users and require some *R*-experience!
174	Create new variables	Create new variables
175	Select data types to include	Select data types to include
176	Uploaded data overview	Uploaded data overview
177	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.
178	Specify covariables	Specify covariables
179	If none are selected, all are included.	If none are selected, all are included.
180	Analyse	Analyse
181	Working...	Working...
182	Press 'Analyse' to create the regression model and after changing parameters.	Press 'Analyse' to create the regression model and after changing parameters.
183	Show p-value	Show p-value
184	Model checks	Model checks
185	Please confirm data reset!	Please confirm data reset!
186	Import data from REDCap	Import data from REDCap
187	REDCap server	REDCap server
188	Web address	Web address
189	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/'
190	API token	API token
191	The token is a string of 32 numbers and letters.	The token is a string of 32 numbers and letters.
192	Connect	Connect
193	Data import parameters	Data import parameters
194	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
195	Import	Import
196	Click to see data dictionary	Click to see data dictionary
197	Connected to server!	Connected to server!
198	The {data_rv$info$project_title} project is loaded.	The {data_rv$info$project_title} project is loaded.
199	Data dictionary	Data dictionary
200	Preview:	Preview:
201	Imported data set	Imported data set
202	Select fields/variables to import:	Select fields/variables to import:
203	Specify the data format	Specify the data format
204	Fill missing values?	Fill missing values?
205	Requested data was retrieved!	Requested data was retrieved!
206	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.
207	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.
208	Click to see the imported data	Click to see the imported data
209	Regression table	Regression table
210	Import a dataset from an environment	Import a dataset from an environment
211	Select a dataset:	Select a dataset:
212	List of datasets...	List of datasets...
213	No data selected!	No data selected!
214	No dataset here...	No dataset here...
215	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.
216	Not a data.frame	Not a data.frame
217	Select source	Select source
218	Select a data source:	Select a data source:
219	Yes	Yes
220	No	No
221	Coefficient plot	Coefficient plot
222	Select outcome variable	Select outcome variable
223	Choose regression analysis	Choose regression analysis
224	Covariables to format as categorical	Covariables to format as categorical
225	Select variable to stratify baseline	Select variable to stratify baseline
226	Select models to plot	Select models to plot
227	Creating regression models failed with the following error:	Creating regression models failed with the following error:
228	Creating a regression table failed with the following error:	Creating a regression table failed with the following error:
229	Saving the plot. Hold on for a moment..	Saving the plot. Hold on for a moment..
230	Running model assumptions checks failed with the following error:	Running model assumptions checks failed with the following error:
231	Select checks to plot	Select checks to plot
232	Multivariable regression model checks	Multivariable regression model checks
233	Grouped by {get_label(data,ter)}	Grouped by {get_label(data,ter)}
234	Option to perform statistical comparisons between strata in baseline table.	Option to perform statistical comparisons between strata in baseline table.
235	Press 'Evaluate' to create the comparison table.	Press 'Evaluate' to create the comparison table.
236	The data includes {n_col} variables. Please limit to 100.	The data includes {n_col} variables. Please limit to 100.
237	Data import	Data import
238	Data import formatting	Data import formatting
239	Data modifications	Data modifications
240	Variables filter	Variables filter
241	Data filter	Data filter
242	Data characteristics table	Data characteristics table
243	The dataset without text variables	The dataset without text variables
244	Creating the table. Hold on for a moment..	Creating the table. Hold on for a moment..
245	Generating the report. Hold on for a moment..	Generating the report. Hold on for a moment..
246	We encountered the following error showing missingness:	We encountered the following error showing missingness:
247	We encountered the following error browsing your data:	We encountered the following error browsing your data:
248	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.
249	Other	Other
250	Hour of the day	Hour of the day
251	Breaks	Breaks
252	By day of the week	By day of the week
253	By weekday	By weekday
254	By week number and year	By week number and year
255	By week number	By week number
256	By month and year	By month and year
257	By month only	By month only
258	By quarter of the year	By quarter of the year
259	By year	By year
260	Keep only most common	Keep only most common
261	Number	Number
262	Combine below percentage	Combine below percentage
263	Percentage	Percentage
264	By specified numbers	By specified numbers
265	By quantiles (groups of equal size)	By quantiles (groups of equal size)
266	Please fill in web address and API token, then press 'Connect'.	Please fill in web address and API token, then press 'Connect'.
267	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.
268	Text or character to split string by	Text or character to split string by
269	Split the variable	Split the variable
270	Variable to split:	Variable to split:
271	Direction:	Direction:
272	Split string to multiple columns. Keep number of rows.	Split string to multiple columns. Keep number of rows.
273	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
274	Split character string	Split character string
275	Split text	Split text
276	Split a character string by a common delimiter	Split a character string by a common delimiter
277	Select delimiter	Select delimiter
278	Browse data preview	Browse data preview
279	Original data	Original data
280	Preview of result	Preview of result
281	No character variables with accepted delimiters detected.	No character variables with accepted delimiters detected.
282	Split a text column by a recognised delimiter.	Split a text column by a recognised delimiter.
283	Apply split	Apply split
284	Stacked relative barplot	Stacked relative barplot
285	Create relative stacked barplots to show the distribution of categorical levels	Create relative stacked barplots to show the distribution of categorical levels
286	Side-by-side barplot	Side-by-side barplot
287	Create side-by-side barplot to show the distribution of categorical levels	Create side-by-side barplot to show the distribution of categorical levels
288	Select table theme	Select table theme
289	Level of detail	Level of detail
290	Minimal	Minimal
291	Extensive	Extensive
292	Letters	Letters
293	Words	Words
294	Shorten to first letters	Shorten to first letters
295	Shorten to first words	Shorten to first words
296	Missings across variables by the variable **'{input$missings_var}'**	Missings across variables by the variable **'{input$missings_var}'**
297	Missing vs non-missing observations in the variable **'{input$missings_var}'**	Missing vs non-missing observations in the variable **'{input$missings_var}'**
298	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.
299	Calculating. Hold tight for a moment..	Calculating. Hold tight for a moment..
300	Overview of missing observations	Overview of missing observations
301	Analysis method for missingness overview	Analysis method for missingness overview
302	Overview of missings across variables	Overview of missings across variables
303	Overview of difference in variables by missing status in outcome	Overview of difference in variables by missing status in outcome
304	Select a variable for grouped overview	Select a variable for grouped overview
305	Select outcome variable for overview	Select outcome variable for overview
306	No outcome measure chosen	No outcome measure chosen
307	There is a significant difference in data missingness in {n_nonmcar} {ifelse(n_nonmcar==1,'variable','variables')} grouped by the selected outcome/grouping variable {outcome}.	There is a significant difference in data missingness in {n_nonmcar} {ifelse(n_nonmcar==1,'variable','variables')} grouped by the selected outcome/grouping variable {outcome}.
308	Include group differences	Include group differences
309	Error:	Error:
310	Download table	Download table
311	Welcome to FreesearchR	Welcome to FreesearchR
312	A free data analysis tool for clinicians, students, and learners	A free data analysis tool for clinicians, students, and learners
313	Core Features	Core Features
314	Import Data	Import Data
315	Data Management	Data Management
316	Filter, modify, and create new variables. Prepare your data efficiently for analysis.	Filter, modify, and create new variables. Prepare your data efficiently for analysis.
317	Descriptive Statistics	Descriptive Statistics
318	Additional Capabilities	Additional Capabilities
319	Data Visualization	Data Visualization
320	Create simple, clean plots for quick insights and overview	Create simple, clean plots for quick insights and overview
321	Regression Models	Regression Models
322	Build simple regression models for advanced analysis	Build simple regression models for advanced analysis
323	Export & Learn	Export & Learn
324	Download Results	Download Results
325	Get Modified Data	Get Modified Data
326	Reproducible Code	Reproducible Code
327	Full Documentation	Full Documentation
328	Share Feedback	Share Feedback
329	Contact Us	Contact Us
330	FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org	FreesearchR is available in multiple languages. To help with translations, please contact us at info@freesearchr.org
331	Home	Home
332	Start with FreesearchR for basic data evaluation and analysis.	Start with FreesearchR for basic data evaluation and analysis.
333	When you need more advanced tools, you'll be better prepared to use R directly.	When you need more advanced tools, you'll be better prepared to use R directly.
334	(Read more)	(Read more)
335	Run the FreesearchR app locally when working with sensitive data.	Run the FreesearchR app locally when working with sensitive data.
336	Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility.	Load data from spreadsheets, REDCap servers, or try with sample data. Multiple sources supported for maximum flexibility.
337	Evaluate data with descriptive analyses, inspect correlations, and review missing observations effectively.	Evaluate data with descriptive analyses, inspect correlations, and review missing observations effectively.
338	Export results directly to your text editor	Export results directly to your text editor
339	Save your processed datasets for later	Save your processed datasets for later
340	Learn and reproduce results in R	Learn and reproduce results in R
341	When you need more advanced tools, you'll be prepared to use R directly.	When you need more advanced tools, you'll be prepared to use R directly.