Binary logistic regression using Stata syntax (March 2021)

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This video walks you through steps for performing binary logistic regression. In particular, I review code written into a do-file for generating results associated with various analyses. All analyses were performed using Stata version 14.
A copy of the stata data file can be downloaded here:
drive.google.com/file/d/1YisZ...
A copy of the do-file referenced in the video can be downloaded here:
drive.google.com/file/d/1pSxW...
A copy of the Powerpoint referenced in the video can be downloaded here:
drive.google.com/file/d/19MXz...
See my video on generating partially and fully standardized regression slopes using the 'spost13' package here: • How to easily generate...
For additional videos and resources on multivariate statistics, check out: sites.google.com/view/statist...

Опубликовано:

7 авг 2024

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Комментарии : 11

@thyveun7685 2 месяца назад

Thank you so much for sharing

@Carlito_Sway Год назад

Thank you for this great video- very straightforward and helpful! I especially appreciate the information about interpreting the logit regression coefficients as a scale of movement towards a binary outcome (and the information about the pseudo-R^2!).

@mikecrowson2462 Год назад

Glad it was helpful!

@juliaspaczynska567 5 месяцев назад

Thank you! Absolutely best Stata guidance!

@iqbalmarri3192 3 года назад

thank you very much sir for ppt and do file

@hangangthu2361 2 года назад

Thank you for your sharing

@johnsonmshiu4837 2 года назад

For the case of conditional logistic regression is necessary to check for the model fit (Hosmer and Lameshow test)

@ashrafulalam483 Год назад

Great Help

@fanaaraf8663 Год назад

Hi Mike! Thank you for such an informative video. My data has over 240k observation and I ran pearson chi square gof test, my p-value is 0.000. How do I fix this issue? Please advise. I also ran lroc command and got roc as 0.7518. This indicates a good fit, right? Does the rejection from pearson gof test matter? (I also ran hl test and was rejected, but I read it is not valid for large sample size).