Your English writing platform
Discover LudwigSuggestions(2)
Exact(17)
We introduce new model-based procedures for replacing these values with reasonable numbers, so that the completed data set is ready for use with statistical analysis methods that rely on complete data, such as regression or classification with high-dimensional explanatory variables.
The best linear unbiased predictors (BLUP) were calculated to create, in effect, a completed data set (Piepho 1998; Balzarini 2002; Piepho and Möhring 2006; Piepho et al. 2008).
In each analysis, the number of students included may differ depending on how many students had a completed data set for that particular analysis.
Our MI procedure replaces missing values of union membership with multiple sets of simulated values to complete the data, applies standard regression techniques (OLS; FE; CRE_Poisson) to analyse each completed data set and adjusts the obtained parameter estimates for missing-data uncertainty by means of Rubin's Rules.
After MI, each completed data set was analysed separately and results combined using standard Rubin's rules.
A sensitivity analysis on the completed data set for these five factors showed quantitatively similar results.
Similar(43)
Completed data sets were obtained from 20 patients.
This is done m times, generating m completed data sets.
This method "fills in" plausible values for the missing data, creating five imputed (completed) data sets.
All statistical analyses of the patient outcome data are based upon the 61 completed data sets.
Every analysis in our study was performed once for every completed data-set, and then the results were averaged according to Rubin's (1987) formula.
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