Handling missing values in Stata Using Mean imputation on Panel Data

In this tutorial, we'll explore a common technique for handling missing values in Stata: mean imputation. When we encounter missing data in our datasets, we need to decide how to deal with those missing values before we can analyze the data. Mean imputation is a simple and widely used approach that involves replacing missing values with the mean value of the non-missing observations in the same variable.
We'll walk through the steps of identifying missing values in our dataset, calculating the mean for each variable with missing values, and then using the "egen" command in Stata to replace the missing values with the mean. We'll also discuss some of the limitations and potential biases of this technique, as well as some alternatives to consider.
By the end of this tutorial, you'll have a better understanding of how to handle missing data in Stata using mean imputation, and the implications of doing so for your analysis. Whether you're a student, researcher, or data analyst, this tutorial will provide you with a useful tool for dealing with missing values in your Stata projects.
Files
1.Dataset used : drive.google.c...
Original raw data : www.kaggle.com...
2.Do-file
drive.google.c...

[@christineakello5143]

Very informative

[@IjazAhmad-kh3hy]

Hi Wilfred, thank you for the video. But you have described how the process applies to panel data.

[@sty8089]

Great video! Thank you!

[@paulsiekisa]

Nice tutorial buddy keep it up

[@wilfred.theanalyst]

Thank you so much

[@Islam101_Uganda]

Thanks for the video. Why haven't you first found out if the data is MCAR, MAR or MNAR?

[@user-jy4cp3ph4e]

Thank you sir for this video. How do we deal if its a missing categorical variable?

[@wilfred.theanalyst]

Sorry for categorical variables I haven't posted the video yet but there is a special way on how to handle them.

[@panagiotatsagkali2]

great video, thank you! what can someone do if they want to select for example the GDP growth of a specific country while having more than one country?

[@wilfred.theanalyst]

You can just filter so as to have cros-section data instead of panel/longtitudinal data.If you need help I can demonstrate via zoom meeting.

[@panagiotatsagkali2]

@@wilfred.theanalyst Thank you so much, I've found it :)

[@wilfred.theanalyst]

@@panagiotatsagkali2 You're welcome

[@honorab.akodegnondjidonou3692]

@@wilfred.theanalyst wilfred thank for your video, I need help gen No_Alldeath_mean= mean(No_Alldeath) but my said unknown function mean() what can I do

[@wilfred.theanalyst]

@@honorab.akodegnondjidonou3692 Sorry, unfortunately 'mean( )' function in Stata is used to calculate the mean of a variable withinn a dataset i.e mean(No_ALLDEATH) ,but it cannot be directly used to create a new variable. However, based on the above you can use this command and it will give you a new column with the mean 'egen No_Alldeath=mean(No_ALLDEATH) '

[@christineakello5143]

Hi Wilfred, do you do private tutorials?

[@wilfred.theanalyst]

Yes I do have private tutorials. Reach me via email: [e-mail]

[@atifdai313]

Dear Wilfred...........The file Missing_PanelData is not opening in stata.Please update this file in stata as well as in excel.

[@wilfred.theanalyst]

Hi,the file is up to date.Kindly download it first then open it.Its working 100% .Cheers!

[@atifdai313]

@@wilfred.theanalyst GREAT

[@atifdai313]

@@wilfred.theanalyst Everything is fine but how_many_imputations is showing an error..........showing the following results. Fraction of missing information (95% CI): . ( ., .) Imputations in pilot: . Imputations needed: . Imputations to add: 0