diff --git a/articles/Automatic_Regression_Modeling.html b/articles/Automatic_Regression_Modeling.html index bbcfd0b..d05822f 100644 --- a/articles/Automatic_Regression_Modeling.html +++ b/articles/Automatic_Regression_Modeling.html @@ -125,7 +125,7 @@

Linear model with multiple variabl

You can make a publication-ready table easily using myft(). It makes a flextable object which can use in HTML, PDF, microsoft word or powerpoint file.

 autoReg(fit) %>% myft()
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You can also use three or more grouping variables.The resultant table will be too long to review, but you can try.

 gaze(sex+DM+HBP~age,data=acs) %>% myft()
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If you do not want to show the reference values in table, you can shorten the table.

 shorten(result) %>% myft()
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If you want to include all explanatory variables in the multivariate model, just set the threshold 1.

 autoReg(fit, uni=TRUE,threshold=1) %>% myft()
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You can perform stepwise backward elimination to select variables and make a final model. Just set final=TRUE.

 autoReg(fit, uni=TRUE,threshold=1, final=TRUE) %>% myft()
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You can select whether or not show total column.

 gaze(sex+Dx~.,data=acs,show.total=TRUE) %>% myft()
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If there is no missing data, show the table summarizing missing numbers.

gaze(sex~.,data=acs,missing=TRUE) %>% myft()
 There is no missing data in column 'sex'
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