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	Number of breaks:	Number of breaks:
53	Close intervals on the right	Close intervals on the right
54	Include lowest value	Include lowest value
55	Create factor variable	Create factor variable
56	Fixed breaks:	Fixed breaks:
57	Method:	Method:
58	Convert Numeric to Factor	Convert Numeric to Factor
59	Unique:	Unique:
60	Missing:	Missing:
61	Most Common:	Most Common:
62	Min:	Min:
63	Mean:	Mean:
64	Max:	Max:
65	Decimal separator:	Decimal separator:
66	First five rows are shown below:	First five rows are shown below:
67	Imported data	Imported data
68	www/intro.md	www/intro.md
69	Choose your data	Choose your data
70	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.
71	Factor variable to reorder:	Factor variable to reorder:
72	Sort by levels	Sort by levels
73	Sort by count	Sort by count
74	Create a new variable (otherwise replaces the one selected)	Create a new variable (otherwise replaces the one selected)
75	Update factor variable	Update factor variable
76	Sort count	Sort count
77	Levels	Levels
78	Count	Count
79	Update levels of a factor	Update levels of a factor
80	Update & select variables	Update & select variables
81	Date format:	Date format:
82	Date to use as origin to convert date/datetime:	Date to use as origin to convert date/datetime:
83	Apply changes	Apply changes
84	No data to display.	No data to display.
85	Data successfully updated!	Data successfully updated!
86	You removed {p_out} % of observations.	You removed {p_out} % of observations.
87	You removed {p_out} % of variables.	You removed {p_out} % of variables.
88	You can import {file_extensions_text} files	You can import {file_extensions_text} files
89	You can choose between these file types:	You can choose between these file types:
90	Rows to skip before reading data:	Rows to skip before reading data:
91	Missing values character(s):	Missing values character(s):
92	if several use a comma (',') to separate them	if several use a comma (',') to separate them
93	Encoding:	Encoding:
94	Upload a file:	Upload a file:
95	Browse...	Browse...
96	Select sheet to import:	Select sheet to import:
97	No file selected.	No file selected.
98	Evaluate	Evaluate
99	Visuals	Visuals
100	Regression	Regression
101	Download	Download
102	{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.
103	Prepare	Prepare
104	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.
105	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.
106	No variables have a correlation measure above the threshold.	No variables have a correlation measure above the threshold.
107	and	and
108	from each pair	from each pair
109	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.
110	Plot	Plot
111	Adjust settings, then press "Plot".	Adjust settings, then press "Plot".
112	Plot height (mm)	Plot height (mm)
113	Plot width (mm)	Plot width (mm)
114	File format	File format
115	Download plot	Download plot
116	Select variable	Select variable
117	Response variable	Response variable
118	Plot type	Plot type
119	Please select	Please select
120	Additional variables	Additional variables
121	Secondary variable	Secondary variable
122	No variable	No variable
123	Grouping variable	Grouping variable
124	No stratification	No stratification
125	Drawing the plot. Hold tight for a moment..	Drawing the plot. Hold tight for a moment..
126	#Plotting\n	#Plotting\n
127	Stacked horizontal bars	Stacked horizontal bars
128	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
129	Violin plot	Violin plot
130	A modern alternative to the classic boxplot to visualise data distribution	A modern alternative to the classic boxplot to visualise data distribution
131	Sankey plot	Sankey plot
132	A way of visualising change between groups	A way of visualising change between groups
133	Scatter plot	Scatter plot
134	A classic way of showing the association between to variables	A classic way of showing the association between to variables
135	Box plot	Box plot
136	A classic way to plot data distribution by groups	A classic way to plot data distribution by groups
137	Euler diagram	Euler diagram
138	Generate area-proportional Euler diagrams to display set relationships	Generate area-proportional Euler diagrams to display set relationships
139	Documentation	Documentation
140	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.
141	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.
142	Feedback	Feedback
143	License: AGPLv3	License: AGPLv3
144	Source	Source
145	Data includes {n_pairs} pairs of highly correlated variables.	Data includes {n_pairs} pairs of highly correlated variables.
146	Create plot	Create plot
147	Coefficients plot	Coefficients plot
148	Checks	Checks
149	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.
150	Browse observations	Browse observations
151	Settings	Settings
152	The following error occured on determining correlations:	The following error occured on determining correlations:
153	We encountered the following error creating your report:	We encountered the following error creating your report:
154	No variable chosen for analysis	No variable chosen for analysis
155	No missing observations	No missing observations
156	Missing vs non-missing observations in the variable **'{variabler()}'**	Missing vs non-missing observations in the variable **'{variabler()}'**
157	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}.
158	There is a total of {p_miss} % missing observations.	There is a total of {p_miss} % missing observations.
159	Median:	Median:
160	Restore original data	Restore original data
161	Reset to original imported dataset. Careful! There is no un-doing.	Reset to original imported dataset. Careful! There is no un-doing.
162	Characteristics	Characteristics
163	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.
164	Compare strata?	Compare strata?
165	Correlations	Correlations
166	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'.
167	Correlation cut-off	Correlation cut-off
168	Set the cut-off for considered 'highly correlated'.	Set the cut-off for considered 'highly correlated'.
169	Missings	Missings
170	Class	Class
171	Observations	Observations
172	Data classes and missing observations	Data classes and missing observations
173	Sure you want to reset data? This cannot be undone.	Sure you want to reset data? This cannot be undone.
174	Cancel	Cancel
175	Confirm	Confirm
176	The filtered data	The filtered data
177	Create new factor	Create new factor
178	This window is aimed at advanced users and require some *R*-experience!	This window is aimed at advanced users and require some *R*-experience!
179	Create new variables	Create new variables
180	Select data types to include	Select data types to include
181	Uploaded data overview	Uploaded data overview
182	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.
183	Specify covariables	Specify covariables
184	If none are selected, all are included.	If none are selected, all are included.
185	Analyse	Analyse
186	Working...	Working...
187	Press 'Analyse' to create the regression model and after changing parameters.	Press 'Analyse' to create the regression model and after changing parameters.
188	Show p-value	Show p-value
189	Model checks	Model checks
190	Please confirm data reset!	Please confirm data reset!
191	Import data from REDCap	Import data from REDCap
192	REDCap server	REDCap server
193	Web address	Web address
194	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/'
195	API token	API token
196	The token is a string of 32 numbers and letters.	The token is a string of 32 numbers and letters.
197	Connect	Connect
198	Data import parameters	Data import parameters
199	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
200	Import	Import
201	Click to see data dictionary	Click to see data dictionary
202	Connected to server!	Connected to server!
203	The {data_rv$info$project_title} project is loaded.	The {data_rv$info$project_title} project is loaded.
204	Data dictionary	Data dictionary
205	Preview:	Preview:
206	Imported data set	Imported data set
207	Select fields/variables to import:	Select fields/variables to import:
208	Specify the data format	Specify the data format
209	Fill missing values?	Fill missing values?
210	Requested data was retrieved!	Requested data was retrieved!
211	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.
212	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.
213	Click to see the imported data	Click to see the imported data
214	Regression table	Regression table
215	Import a dataset from an environment	Import a dataset from an environment
216	Select a dataset:	Select a dataset:
217	List of datasets...	List of datasets...
218	No data selected!	No data selected!
219	No dataset here...	No dataset here...
220	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.
221	Not a data.frame	Not a data.frame
222	Select source	Select source
223	Select a data source:	Select a data source:
224	Yes	Yes
225	No	No
226	Coefficient plot	Coefficient plot
227	Select outcome variable	Select outcome variable
228	Choose regression analysis	Choose regression analysis
229	Covariables to format as categorical	Covariables to format as categorical
230	Select variable to stratify baseline	Select variable to stratify baseline
231	Select models to plot	Select models to plot
232	Creating regression models failed with the following error:	Creating regression models failed with the following error:
233	Creating a regression table failed with the following error:	Creating a regression table failed with the following error:
234	Saving the plot. Hold on for a moment..	Saving the plot. Hold on for a moment..
235	Running model assumptions checks failed with the following error:	Running model assumptions checks failed with the following error:
236	Select checks to plot	Select checks to plot
237	Multivariable regression model checks	Multivariable regression model checks
238	Grouped by {get_label(data,ter)}	Grouped by {get_label(data,ter)}
239	Option to perform statistical comparisons between strata in baseline table.	Option to perform statistical comparisons between strata in baseline table.
240	Press 'Evaluate' to create the comparison table.	Press 'Evaluate' to create the comparison table.
241	The data includes {n_col} variables. Please limit to 100.	The data includes {n_col} variables. Please limit to 100.
242	Data import	Data import
243	Data import formatting	Data import formatting
244	Data modifications	Data modifications
245	Variables filter	Variables filter
246	Data filter	Data filter
247	Data characteristics table	Data characteristics table
248	The dataset without text variables	The dataset without text variables
249	Creating the table. Hold on for a moment..	Creating the table. Hold on for a moment..
250	Select variable to stratify analysis	Select variable to stratify analysis
251	Generating the report. Hold on for a moment..	Generating the report. Hold on for a moment..
252	We encountered the following error showing missingness:	We encountered the following error showing missingness:
253	We encountered the following error browsing your data:	We encountered the following error browsing your data:
254	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.
255	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.
256	Other	Other
257	Hour of the day	Hour of the day
258	Breaks	Breaks
259	By day of the week	By day of the week
260	By weekday	By weekday
261	By week number and year	By week number and year
262	By week number	By week number
263	By month and year	By month and year
264	By month only	By month only
265	By quarter of the year	By quarter of the year
266	By year	By year
267	Keep only most common	Keep only most common
268	Number	Number
269	Combine below percentage	Combine below percentage
270	Percentage	Percentage
271	By specified numbers	By specified numbers
272	By quantiles (groups of equal size)	By quantiles (groups of equal size)
273	Please fill in web address and API token, then press 'Connect'.	Please fill in web address and API token, then press 'Connect'.
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.