Your English writing platform
Discover LudwigSimilar(60)
Missing data is a problem that is ubiquitous to all clinical studies and a source of multiple problems from an analytic point of view (reduced statistical power, increased the type I error, bias) Statistical approaches have been developed to analyze data collected from trials with missing data.
How to deal with missing data.
Charts with missing data were deleted.
Third, days with missing data are excluded.
Respondents with missing data were also excluded.
Variables with missing data are listed.
Variables with missing data were dummy coded using the missing-indicator method.
Missing indicator method was used to analyze categorical variables with missing data.
We used multiple imputation to deal with missing data.
Thus, we replaced missing data values with the mean for that variable instead of excluding patients with missing data.
Patients with missing data.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com