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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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inst/translations/translation_sw.csv
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@ -150,7 +150,6 @@
"Settings","Settings"
"The following error occured on determining correlations:","The following error occured on determining correlations:"
"We encountered the following error creating your report:","We encountered the following error creating your report:"
"No variable chosen for analysis","No variable chosen for analysis"
"No missing observations","No missing observations"
"There is a total of {p_miss} % missing observations.","There is a total of {p_miss} % missing observations."
"Median:","Median:"
@ -244,7 +243,6 @@
"Data characteristics table","Data characteristics table"
"The dataset without text variables","The dataset without text variables"
"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 showing missingness:","We encountered the following error showing missingness:"
"We encountered the following error browsing your data:","We encountered the following error browsing your data:"
@ -296,11 +294,15 @@
"Words","Words"
"Shorten to first letters","Shorten to first letters"
"Shorten to first words","Shorten to first words"
"Select missings analysis to apply","Select missings analysis to apply"
"Variables","Variables"
"By outcome","By outcome"
"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.."
"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}."
"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 sw
150 Settings Settings
151 The following error occured on determining correlations: The following error occured on determining correlations:
152 We encountered the following error creating your report: We encountered the following error creating your report:
No variable chosen for analysis No variable chosen for analysis
153 No missing observations No missing observations
154 There is a total of {p_miss} % missing observations. There is a total of {p_miss} % missing observations.
155 Median: Median:
243 Data characteristics table Data characteristics table
244 The dataset without text variables The dataset without text variables
245 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
246 Generating the report. Hold on for a moment.. Generating the report. Hold on for a moment..
247 We encountered the following error showing missingness: We encountered the following error showing missingness:
248 We encountered the following error browsing your data: We encountered the following error browsing your data:
294 Words Words
295 Shorten to first letters Shorten to first letters
296 Shorten to first words Shorten to first words
Select missings analysis to apply Select missings analysis to apply
Variables Variables
By outcome By outcome
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 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}. Overview of missing observations 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}. 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}.