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  • suest - variance matrix is nonsymmetric or highly singular

    I fit the full multinomial logit model for all four alternatives of my response variable and four restricted multinomial models in which one alternative is excluded:

    estimates dir

    ---------------------------------------------------------------------------------------
    name | command depvar npar title
    -------------+-------------------------------------------------------------------------
    m1 | mlogit IntlFW 280 all four
    m2 | mlogit IntlFW 280 IntlFW != No Intl FW :IntlFW
    m3 | mlogit IntlFW 280 IntlFW != AA1000 only :IntlFW
    m4 | mlogit IntlFW 280 IntlFW != ISAE3000 only :IntlFW
    m5 | mlogit IntlFW 280 IntlFW != Both AA1000 & ISAE3000 :IntlFW
    ---------------------------------------------------------------------------------------


    I then increased the matsize to 800 (I have Stata IC) and the used the following code to conduct the suest test:

    suest m1 m2, vce(cluster CompanyName) noomitted

    However, I am getting the following warning and an empty results table: "Warning: variance matrix is nonsymmetric or highly singular"

    I also used dataex to include some of my data with this question, but I Stata is giving me the following response:
    dataex IntlFW i.NumTypeofAP GeoRevSeg ROA LMarketCap DisclosureIndex MandatedAssurance i.FSaud
    > itorCode i.SVCGrouped i.NumHQ i.Fiscalyear, count(150)
    factor variables and time-series operators not allowed
    r(101);

    Do you know what the warning in red above means and what I can do to get a proper response for my suest test? I would be very grateful for some help.

  • #2
    Sunita:
    I do hope that the following (old) thread can be helpful: https://www.stata.com/statalist/arch.../msg00980.html.
    Kind regards,
    Carlo
    (StataNow 18.5)

    Comment


    • #3
      Hi Carlo,

      It is very kind of you to send a link to that thread.

      So, I should remove the "problem" predictor variables? I have an idea which ones they are.

      Warm Regards,
      Sunita

      Comment


      • #4
        Sunita:
        I'm sorry, no.
        You should check your dataset and spot the sparse ones (usually they're categorical variables).
        Kind regards,
        Carlo
        (StataNow 18.5)

        Comment


        • #5
          Hi Carlo,

          Thank you so much for this suggestion.

          I have not done that before. Could point me in the right direction?

          Warm Regards,
          Sunita

          Comment


          • #6
            Sunita:
            for instance, a categorical variables that can take on 0/1 values but scores 1 for a too limited proportion of the sample (summed up from https://www.stata.com/statalist/arch.../msg00980.html).
            Kind regards,
            Carlo
            (StataNow 18.5)

            Comment


            • #7
              Hi Carlo,

              This is very useful. I will examine all my indicator variables asap.

              Warm Regards,
              Sunita

              Comment


              • #8
                Hi Carlo,

                Thank you so much for your kindness!

                I examined all my indicator variables and none of them seem sparse to me.

                I have a total of 4438 observations. If there are 217 missing observations from a total of 4438 (as in the variable FSauditorCode below), it that considered sparse?

                I would be very grateful for your guidance and opinion.


                codebook IntlFW MandatedAssurance FSauditorCode SVCGrouped NumHQ Fiscalyear

                ------------------------------------------------------------------------------------------------
                IntlFW
                ------------------------------------------------------------------------------------------------

                type: numeric (byte)
                label: Intl

                range: [0,3] units: 1
                unique values: 4 missing .: 66/4,438

                tabulation: Freq. Numeric Label
                1,445 0 No Intl FW
                892 1 AA1000 only
                1,625 2 ISAE3000 only
                410 3 Both AA1000 & ISAE3000
                66 .

                ------------------------------------------------------------------------------------------------
                MandatedAssurance (unlabeled)
                ------------------------------------------------------------------------------------------------

                type: numeric (byte)

                range: [0,1] units: 1
                unique values: 2 missing .: 0/4,438

                tabulation: Freq. Value
                3,972 0
                466 1

                ------------------------------------------------------------------------------------------------
                FSauditorCode FSauditorCode
                ------------------------------------------------------------------------------------------------

                type: numeric (byte)
                label: FSauditorCode

                range: [0,2] units: 1
                unique values: 3 missing .: 66/4,438
                unique mv codes: 2 missing .*: 151/4,438

                tabulation: Freq. Numeric Label
                457 0 All auditors non-Big4
                155 1 Mix of Big4 and non-Big4
                3,609 2 All Big4
                66 .
                151 .n

                ------------------------------------------------------------------------------------------------
                SVCGrouped RECODE of svcInd
                ------------------------------------------------------------------------------------------------

                type: numeric (byte)
                label: SVCInd

                range: [1,5] units: 1
                unique values: 5 missing .: 66/4,438

                tabulation: Freq. Numeric Label
                306 1 Mining
                1,860 2 Manufacturing
                402 3 Utilities
                789 4 Finance
                1,015 5 Other
                66 .

                ------------------------------------------------------------------------------------------------
                NumHQ HQ Country
                ------------------------------------------------------------------------------------------------

                type: numeric (byte)
                label: NumHQ

                range: [1,45] units: 1
                unique values: 45 missing .: 66/4,438

                examples: 12 France
                21 Japan
                35 South Africa
                41 Taiwan

                ------------------------------------------------------------------------------------------------
                Fiscalyear Fiscal year
                ------------------------------------------------------------------------------------------------

                type: numeric (int)

                range: [2008,2015] units: 1
                unique values: 8 missing .: 0/4,438

                tabulation: Freq. Value
                208 2008
                281 2009
                439 2010
                581 2011
                583 2012
                814 2013
                883 2014
                649 2015

                Comment


                • #9
                  Sunita:
                  my temptative answer puts the blame on:
                  Code:
                  MandatedAssurance (unlabeled)
                  ------------------------------------------------------------------------------------------------
                  
                  type: numeric (byte)
                  
                  range: [0,1] units: 1
                  unique values: 2 missing .: 0/4,438
                  
                  tabulation: Freq. Value
                  3,972 0
                  466 1
                  to the prevalence of 0s.
                  Kind regards,
                  Carlo
                  (StataNow 18.5)

                  Comment


                  • #10
                    Hi Carlo,

                    Thank you so much for your help. I greatly appreciate your kindness.

                    Would you recommend dropping the variable MandatedAssurance and running all my models again?

                    Warm Regards,
                    Sunita

                    Comment


                    • #11
                      Sunita:
                      yes, I would give it a try.
                      Kind regards,
                      Carlo
                      (StataNow 18.5)

                      Comment


                      • #12
                        Hi Carlo,

                        Thank you very much for your suggestion. I will do that.

                        Warm Regards,
                        Sunita Rao

                        Comment


                        • #13
                          Dear Sunita,

                          I got the same problem with the multinomial regression. I would like to ask please how did you solve it? I tried to apply Carlo advice of MandatedAssurance but it did not work with me. Thus, Can I ask you please what is the command syntax that needs to be run it in Stata?


                          Many thanks for your kind help in advance

                          Best regards,
                          Rabab

                          Comment


                          • #14
                            Duplicate post. See reply at: https://www.statalist.org/forums/for...ighly-singular
                            Kind regards,
                            Carlo
                            (StataNow 18.5)

                            Comment


                            • #15
                              Hi Carlo,

                              I apologize profusely for taking so long to get back to you.

                              It discussed this issue with my co-author. It turns out that we need to keep MandatedAssurance in our model for theoretical reasons.

                              A Big Thank you for giving me advice. I will certainly keep it in mind if I do multinomial regression.

                              Warm Regards,
                              Sunita

                              Comment

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