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refined missingness evaluation

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Andreas Gammelgaard Damsbo 2025-12-11 17:22:47 +01:00
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17
app_docker/translations/translation_sv.csv
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@ -103,9 +103,7 @@
"You can choose between these file types:","You can choose between these file types:"
"You can import {file_extensions_text} files","You can import {file_extensions_text} files"
"First five rows are shown below:","First five rows are shown below:"
"No variable chosen for analysis","No variable chosen for analysis"
"No missing observations","No missing observations"
"Missing vs non-missing observations in the variable **'{variabler()}'**","Missing vs non-missing observations in the variable **'{variabler()}'**"
"Grouped by {get_label(data,ter)}","Grouped by {get_label(data,ter)}"
"Import data from REDCap","Import data from REDCap"
"REDCap server","REDCap server"
@ -207,7 +205,6 @@
"Correlation cut-off","Correlation cut-off"
"Set the cut-off for considered 'highly correlated'.","Set the cut-off for considered 'highly correlated'."
"Missings","Missings"
"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."
"Visuals","Visuals"
"Analysis validation","Analysis validation"
"Report","Report"
@ -230,7 +227,6 @@
"You removed {p_out} % of observations.","You removed {p_out} % of observations."
"You removed {p_out} % of variables.","You removed {p_out} % of variables."
"There is a total of {p_miss} % missing observations.","There is a total of {p_miss} % missing observations."
"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}."
"Data includes {n_pairs} pairs of highly correlated variables.","Data includes {n_pairs} pairs of highly correlated variables."
"Class","Class"
"Observations","Observations"
@ -267,7 +263,6 @@
"The dataset without text variables","The dataset without text variables"
"The data includes {n_col} variables. Please limit to 100.","The data includes {n_col} variables. Please limit to 100."
"Creating the table. Hold on for a moment..","Creating the table. Hold on for a moment.."
"Select variable to stratify analysis","Select variable to stratify analysis"
"Generating the report. Hold on for a moment..","Generating the report. Hold on for a moment.."
"We encountered the following error creating your report:","We encountered the following error creating your report:"
"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."
@ -299,3 +294,15 @@
"Words","Words"
"Shorten to first letters","Shorten to first letters"
"Shorten to first words","Shorten to first words"
"Missings across variables by the variable **'{input$missings_var}'**","Missings across variables by the variable **'{input$missings_var}'**"
"Missing vs non-missing observations in the variable **'{input$missings_var}'**","Missing vs non-missing observations in the variable **'{input$missings_var}'**"
"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."
"Calculating. Hold tight for a moment..","Calculating. Hold tight for a moment.."
"Overview of missing observations","Overview of missing observations"
"Analysis method for missingness overview","Analysis method for missingness overview"
"Overview of missings across variables","Overview of missings across variables"
"Overview of difference in variables by missing status in outcome","Overview of difference in variables by missing status in outcome"
"Select a variable for grouped overview","Select a variable for grouped overview"
"Select outcome variable for overview","Select outcome variable for overview"
"No outcome measure chosen","No outcome measure chosen"
"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}."

1 en sv
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:
No variable chosen for analysis No variable chosen for analysis
106 No missing observations No missing observations
Missing vs non-missing observations in the variable **'{variabler()}'** Missing vs non-missing observations in the variable **'{variabler()}'**
107 Grouped by {get_label(data,ter)} Grouped by {get_label(data,ter)}
108 Import data from REDCap Import data from REDCap
109 REDCap server REDCap server
205 Correlation cut-off Correlation cut-off
206 Set the cut-off for considered 'highly correlated'. Set the cut-off for considered 'highly correlated'.
207 Missings Missings
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.
208 Visuals Visuals
209 Analysis validation Analysis validation
210 Report Report
227 You removed {p_out} % of observations. You removed {p_out} % of observations.
228 You removed {p_out} % of variables. You removed {p_out} % of variables.
229 There is a total of {p_miss} % missing observations. There is a total of {p_miss} % missing observations.
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}.
230 Data includes {n_pairs} pairs of highly correlated variables. Data includes {n_pairs} pairs of highly correlated variables.
231 Class Class
232 Observations Observations
263 The dataset without text variables The dataset without text variables
264 The data includes {n_col} variables. Please limit to 100. The data includes {n_col} variables. Please limit to 100.
265 Creating the table. Hold on for a moment.. Creating the table. Hold on for a moment..
Select variable to stratify analysis Select variable to stratify analysis
266 Generating the report. Hold on for a moment.. Generating the report. Hold on for a moment..
267 We encountered the following error creating your report: We encountered the following error creating your report:
268 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.
294 Words Words
295 Shorten to first letters Shorten to first letters
296 Shorten to first words Shorten to first words
297 Missings across variables by the variable **'{input$missings_var}'** Missings across variables by the variable **'{input$missings_var}'**
298 Missing vs non-missing observations in the variable **'{input$missings_var}'** Missing vs non-missing observations in the variable **'{input$missings_var}'**
299 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.
300 Calculating. Hold tight for a moment.. Calculating. Hold tight for a moment..
301 Overview of missing observations Overview of missing observations
302 Analysis method for missingness overview Analysis method for missingness overview
303 Overview of missings across variables Overview of missings across variables
304 Overview of difference in variables by missing status in outcome Overview of difference in variables by missing status in outcome
305 Select a variable for grouped overview Select a variable for grouped overview
306 Select outcome variable for overview Select outcome variable for overview
307 No outcome measure chosen No outcome measure chosen
308 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}.