[Limdep Nlogit List] Getting standard errors for omitted variables?

Jason Ong doctorjasonong at gmail.com
Fri Jan 3 11:20:23 AEDT 2020


hi,

When I run an MNL model, it gives me outputs of the coefficients for each
attribute level
However, I would also like to get the standard errors (to calculate the 95%
CI) for the omitted/reference level
how could I calculate this?
thank you kindly for your help

Discrete choice (multinomial logit) model

Dependent variable               Choice

Log likelihood function     -3332.83194

Estimation based on N =   7008, K =  14

Inf.Cr.AIC  =   6693.7 AIC/N =     .955

---------------------------------------

            Log likelihood R-sqrd R2Adj

ASCs  only  model must be fit separately

               Use NLOGIT ;...;RHS=ONE$

Note: R-sqrd = 1 - logL/Logl(constants)

Warning:  Model does not contain a full

set of ASCs. R-sqrd is problematic. Use

model setup with ;RHS=one to get LogL0.

---------------------------------------

Response data are given as ind. choices

Number of obs.=  7008, skipped    0 obs

--------+--------------------------------------------------------------------

        |                  Standard            Prob.      95% Confidence

 CHOICEV|  Coefficient       Error       z    |z|>Z*         Interval

--------+--------------------------------------------------------------------

   C20|1|     .40410***      .03059    13.21  .0000      .34413    .46406

   C40|1|    -.46829***      .03070   -15.26  .0000     -.52845   -.40813

   C60|1|   -1.26084***      .03594   -35.08  .0000    -1.33128  -1.19040

ACVEND|1|    -.09467**       .04822    -1.96  .0496     -.18918   -.00017

ACSHEL|1|     .45141***      .05013     9.00  .0000      .35315    .54967

 ACMED|1|     .08191*        .04740     1.73  .0840     -.01099    .17480

ACPHAR|1|     .05906         .05280     1.12  .2633     -.04443    .16255

 ACCBO|1|    -.13720***      .05293    -2.59  .0095     -.24095   -.03345

ACSOPV|1|    -.81479***      .05596   -14.56  .0000     -.92448   -.70510

PLARBR|1|    -.10541***      .03289    -3.21  .0013     -.16986   -.04095

 PSMPL|1|     .04375         .03167     1.38  .1671     -.01832    .10582

 PSMBR|1|     .03257         .03254     1.00  .3168     -.03120    .09635

INFVID|1|    -.06273**       .02688    -2.33  .0196     -.11540   -.01005

INFCHA|1|    -.05929**       .02529    -2.34  .0191     -.10886   -.00972

--------+--------------------------------------------------------------------


*Jason Ong*
Twitter: @DrJasonJOng
PhD, MMed, MBBS, FAChSHM, FRACGP

Sexual Health Physician, Melbourne Sexual Health Centre, Alfred Health
Associate Professor (Hon), London School of Hygiene and Tropical Medicine,
UK
Central Clinical School, Monash University, Australia
Melbourne School of Population and Global Health, University of Melbourne,
Australia
Associate Editor, Sexually Transmitted Infections
Special Issues Editor, Sexual Health
Board Director, ASHM (www.ashm.org.au)
https://protect-au.mimecast.com/s/6NWaCZYM2VFk9JELizttba?domain=lshtm.ac.uk
https://protect-au.mimecast.com/s/RrPzC1WZXriPNV1ohGBJsJ?domain=researchgate.net

If you are more fortunate than others, build a longer table, not a taller
fence.


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