Multiple regression using STATA video 1

[@harielvis]

You are actually educating me. After watching this I will use my Eviews lesser and more of Stata. Thank you for showing the way.

[@tebudlamini3083]

You just saved my thesis, thank you sir!!

[@kimberleykolder2824]

Thanks! You saved my master thesis!

[@conjetapierre8755]

Me too

[@Koji.kc04]

thanks my beautiful guy, helped me so much through my coursework

[@twilightcutiesse]

Wish my prof would have taught like this. Thanks!

[@prarthanatripathy3221]

Nice video Sir !

[@sayedalimsamim551]

Excellent explanation

[@Mandla89]

This was great, thank you so much.

[@OmarAhmed-mt6sc]

Thanks, that is really helpful.

[@tylerbotzon7174]

you sir are a saint

[@enawgawchane2713]

Thank you Very much mike, How to procedure from sum, logit, probit, tab and Rigratition ?

[@chrisisah8006]

Thanks for the video Not sure why my stata app keep reading error loading the dataset after i downloaded it. it appears the format isn't agreeing with my stata12

[@a.k4818]

One question please. In your regression a unit increase in anxiety affects negatively the achievement by 0.16. Alternatively, is it true to say that a 1-unit decrease in anxiety affects positively the achievement?

[@mikecrowson2462]

Basically, there is a negative relationship between the two variables. So higher scores on anxiety are associated with lower achievement scores. By the same token, lower scores on anxiety are associated with higher scores on achievement. You have the basic idea.

[@lucifergaming2229]

no

[@907tanveer]

Thank you, Mike. How do you generate a plot after completing the test

[@ibsachemeda2862]

Don't you have to put " i. " command before the categorical variable ? my instructor always suggest to put i. in front of a categorical variable when regressing.

[@mikecrowson2462]

HI there, Ibsa. I'm assuming you are confused because I didn't use the i. prefix for the gender variable. When you have a binary predictor (such as gender), there is no need to state that it is a factor variable (although it it perfectly ok if you would rather do that). The i. prefix simply will cause Stata to dummy code your factor variable, so that group membership is identifiable on a set of binary predictor variables (each coded 0 and 1). Since in my example gender is already binary and dummy coded 0 and 1, there's no need to request this using the i. prefix (although again, it is ok if you want to do this). Cheers!

[@ibsachemeda2862]

@@mikecrowson2462 Well explained. Thank you

[@jjbug82]

Nice video, Mike! I don't have formal training on statistic but now using it for research, so it's always some confusion that I'd like to seek expert advice. Some quick questions about interpreting the results using the above example: 1) since there are 4 independent variables (or predictors), can the model be described as 'the achievement is significantly associated with gender, SMint and anxiety"? 2) Could the result be interpreted as "the achievement is significantly associated with SMint, AND adjusted for gender, anxiety, MGoal"? thanks in advance!

[@dilshaniranawaka6043]

Could you make a video of "switchr"? Really stuck with the sub pop

[@mbabaziviolet1874]

thanks for educating me

[@niketshah9915]

Sir can you tell the meaning of SMint and MGoals for better interpretation of results

[@jianweisim1029]

SMint = Subject Matter of interest... MGoals = Mastery Goals

[@enkhshurnarmandakh9596]

nice video, could you please share the dataset of it ? thank u

[@cristiansalinas5835]

Why Mgoal is not estadistical significance ?

[@asoabdullah9507]

Thank you for your contribution, I wonder if you are working as a freelancer?

[@sitotagetachew4392]

invisible slide?

[@madsfristednavne9632]

Urgent! How do I find the function of the graph of the Linear regression in Stata?

[@Kmulat]

Can you say, as anxiety levels decrease by .16, achievement goes up by 24%

[@mikecrowson2462]

Hi Kidest, it's been a very long time since I put this video up. Going back and looking at the output, it looks like the unstandardized regression slope for anxiety is -.16. That means that for every one raw score unit increase on anxiety, achievement is predicted to decrease by .16 raw score units. Alternatively, we can say that for every one raw score unit decrease on anxiety, achievement is predicted to increase by .16 raw score units. I'm not sure where you got the 24% you are referring to. If you are asking about the standardized regression slope (Beta column) of -.25, then this is the predicted change in Achievement in standard score (aka z-score units) per standard score increase on the predictor. So, the standardized coefficient of -.25 indicates that for every one z-score unit increase on anxiety, achievement is predicted to decrease by .25 z-score units. I hope this helps!

[@kasadhanasser276]

good