Basic Regression Commands in Stata

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  • เผยแพร่เมื่อ 10 พ.ย. 2024

ความคิดเห็น • 39

  • @mayjuly6015
    @mayjuly6015 8 ปีที่แล้ว

    Thank you, Dr Alan.
    May you be peaceful and successful throughout your life.

  • @yujielian2864
    @yujielian2864 7 ปีที่แล้ว

    The way you explain things is very clear. This video is helpful for undergraduate students like me. Thank you for your video!

    • @smilex3
      @smilex3  7 ปีที่แล้ว

      Than you!

  • @r_pydatascience
    @r_pydatascience 8 ปีที่แล้ว +5

    You are making my life easy. That is very helpful. Thank you.

    • @smilex3
      @smilex3  8 ปีที่แล้ว

      +Mihiretu Molla Thank you!

  • @iftehajulislam8987
    @iftehajulislam8987 8 ปีที่แล้ว

    Very nice and detailed descriptions, speech tempo is easy to catch and the video framing is also wonderful. Thank you so much!!!

  • @stephaniesterner5911
    @stephaniesterner5911 10 ปีที่แล้ว

    Thanks for the help! Great overview for multiple regression within stata

    • @smilex3
      @smilex3  10 ปีที่แล้ว

      Thank you! I'm glad you found the video useful.

  • @ΒασίληςΚουτσούγερας
    @ΒασίληςΚουτσούγερας 7 ปีที่แล้ว

    Thank you very much! This helped me a lot in my survey :) Greetings from Greece!

    • @smilex3
      @smilex3  7 ปีที่แล้ว

      I'm glad the video helped.

  • @Garrettthethief
    @Garrettthethief 7 ปีที่แล้ว

    Thank you, your i.sex explenation helped me a lot.

  • @tcal6831
    @tcal6831 8 ปีที่แล้ว

    Great videos. Thank you for sharing with all.

  • @ssennyondoandrewbrian5810
    @ssennyondoandrewbrian5810 4 ปีที่แล้ว

    thanl you really coz these videos are helping good

  • @khandokermonjurekabir8143
    @khandokermonjurekabir8143 6 ปีที่แล้ว +1

    Thank you so much. Its too much helpful.

  • @thourayabouzid683
    @thourayabouzid683 8 ปีที่แล้ว

    hi Mr Alan. please can you chow how to estimate the fixed-effect panel threshold model(Hansan 1999) ??

  • @elizabethkago4424
    @elizabethkago4424 5 ปีที่แล้ว

    hey....am having a problem in keying in the commands for QUAIDS model in stata. Kindly assist

  • @rajeshshigdel1472
    @rajeshshigdel1472 9 ปีที่แล้ว

    Impressive lecture than you very much learned something

    • @smilex3
      @smilex3  9 ปีที่แล้ว +1

      Rajesh Shigdel I'm glad you found it useful!

  • @AI-ew1rj
    @AI-ew1rj 7 ปีที่แล้ว

    Hi, so when looking at the ANOVA table, how can we know if Males are 1 or 0 ( in a case where we didn't write the code and just has the table....so for example, is the unlisted value=0?)

    • @smilex3
      @smilex3  7 ปีที่แล้ว +1

      There is no way to tell, but in your example, men compared to women, the difference in means is identical except for the sign of the difference. It is even harder to tell if you have an independent variable with more categories, e.g. married, widowed, divorced, separated, and never married. But, if you estimate the marginal effects you can determine all of the raw effect sizes.

    • @AI-ew1rj
      @AI-ew1rj 7 ปีที่แล้ว

      Great, thanks!

  • @AI-ew1rj
    @AI-ew1rj 7 ปีที่แล้ว

    what is the difference between ## ad # command in stata?

  • @drmiasmith
    @drmiasmith 8 ปีที่แล้ว

    This is so helpful!! thank you!

    • @smilex3
      @smilex3  8 ปีที่แล้ว

      Thank you. I'm glad you found this useful.

  • @richardmawulawoeahadzie2307
    @richardmawulawoeahadzie2307 9 ปีที่แล้ว

    How do I make In-sample and out-of-sample predictions in STATA

    • @smilex3
      @smilex3  9 ปีที่แล้ว +1

      richard mawulawoe ahadzie
      Richard, I am not exactly certain what you want, but maybe the following will help.
      regress y x
      predict yhatin if e(sample), xb
      predict yhatout if !e(sample)
      The command -predict- is a model post-estimation command that can be used to create predicted values. You can learn more by typing -help predict- in the command window.
      When you estimate a model Stata creates a temporary marker of the sample used in the model called -e(sample)-. This marker is equal to 0 is an observation was not used in the model and 1 if it was.
      Finally, the exclamation mark "!" means "not" (see -help operator-).
      So, the first predict creates in-sample predicted values stored in the variable "yhatin" and the second creates out-sample predicted values stored in the variable "yhatout".
      Best,
      Alan

    • @richardmawulawoeahadzie2307
      @richardmawulawoeahadzie2307 9 ปีที่แล้ว

      thanks Alan, will try and get back to you

  • @nategrate98
    @nategrate98 4 ปีที่แล้ว

    What is that intro song?

    • @smilex3
      @smilex3  4 ปีที่แล้ว +1

      The White Collar Holler by Stan Rogers, a fabulous Canadian folk singer who unfortunately is no longer alive.

  • @abobakermomed9324
    @abobakermomed9324 7 ปีที่แล้ว

    Thank you very much for this video

    • @smilex3
      @smilex3  7 ปีที่แล้ว +1

      I'm glad you found it helpful.

    • @abobakermomed9324
      @abobakermomed9324 7 ปีที่แล้ว

      Dear Alan
      I have this regression and not sure about what I have done
      and you are an expert, please have a glance:
      Accruals it = α1 + α2((ΔREVit - ΔRECit )/Ait-1) + α3(PPEit/Ait-1) + α4(CFOit/Ait-1) + α5NEG_CFOit + α6((NEG_CFOit * CFOit)/Ait-1) + εit
      all variables are numeric except the last two which are:
      ΔCFOi,tNEG is an indicator variable taking the value of 1 if the change in cash flows from operations is negative and 0 otherwise. CFOi,t*CFONEGi,t is an interaction term which is defined as ΔCFOi,t multiplied by ∆CFONEGi,t.
      I did the following for the last two;
      1:
      gen NEG_CFO =.
      replace NEG_CFO=1 if delta_CFO0
      2:
      gen interaction2_CFO = NEG_CFO*(CFO/lagged_assets)
      and I run the regression
      Is that correct?
      Please your response is highly appreciated

    • @abobakermomed9324
      @abobakermomed9324 7 ปีที่แล้ว

      No response?

    • @smilex3
      @smilex3  7 ปีที่แล้ว

      If you are trying to run a regression with an interaction term, it is better in Stata to use factor notation. For example:
      sysuse auto, clear
      regress mpg c.weight c.weight#c.weight
      margins, at(weight=(1800(200)4800))
      marginsplot, recast(line) recastci(rarea)
      see "help fvvarlist" for more information.

    • @abobakermomed9324
      @abobakermomed9324 7 ปีที่แล้ว

      Alan Neustadtl Thank you very much for your help.

  • @vigneo
    @vigneo 9 ปีที่แล้ว

    Thank you!! :)

    • @smilex3
      @smilex3  9 ปีที่แล้ว

      I'm glad the video was useful!

  • @huynhngoctrong9510
    @huynhngoctrong9510 6 ปีที่แล้ว

    8:40 dummy