Re: negative binomial regression

Posted by Rich Ulrich on May 21, 2019; 4:27pm
URL: http://spssx-discussion.165.s1.nabble.com/negative-binomial-regression-tp5737913p5737928.html

Back to the beginning -- I think you have confused us all by mis-identifying

"Rows" and "columns".  If Death11  is a variable name, then you DO properly

have your dependent and independent variables defined, with a column

(as you look at your data in the editor) being one variable, such as Death11.

And each row is a different ward. But that is not what you wrote, more  than once.

Your question is about the lack of effect of the "/emmeans control" specification.

I don't have a sure answer for that, but I can raise one possibility.

What I can say about that is that I wonder whether your data are too sparse

for a full and proper solution.  Are there any Warnings given?   How many

Deaths are there?  Is this a sizeable number, or is it tiny? You have 30 or more

d.f.  in the predictors.  The total N of 582 is large enough for a regression,

according to one rule-of-thumb, but the rule-of-thumb about predicting

events ("Deaths") says that you should also have a large number of events.

And I wonder, further, about the appropriateness of the model.  If your Wards

do not have the same baseline Ns that are at risk for Death, I think you need

to normalize to get a Death-rate ... which would not, however, be a NegBin

model.

--

Rich Ulrich

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From: SPSSX(r) Discussion <[hidden email]> on behalf of keltre19 <[hidden email]>
Sent: Monday, May 20, 2019 11:50 AM
To: [hidden email]
Subject: negative binomial regression

 

urgent help needed: I am using SPSS 25 to perform a negative binomial
regression on overdispersed data. I am trying to work out the negative
binomial equation/interpretation (582 wards are columns; variables are rows)
= Dependent variable is Deaths 2011 (numeric figure for each 582 wards) +
Independent variables are: categorical treated as factors and the rest are %
proportions treated as covariates.

My Q: controlling for demographics and health variables, it was hypothesised
than an increase in an areas deprivation and farming activities will
statistically increase the risk of ward mortality.

1.      How do I make predictions of deaths as I am at my wits end trying to
figure it out!! Going around and round in circles and getting nowhere :C
2.      The code I am running is not doing what I want it to. I want to look at
deprivation (NIMDM) at 1 (most deprived, and then at other intervals for
comparisons) and see what the predicted deaths are in wards and its
influence this has on the other IVs. But when I run this code below it makes
no difference to running it without the       /EMMEANS
CONTROL=NIMDMrank2010(1) line
3.      Then trying to place them on a scatterplot for comparisons. But when I
run this code which of the 4 variables created do I plot (if any). i know
XPPRED gives me the predicted log counts but how do I make them meaningful
in a figure.

GENLIN deaths11_fig BY farms11code avSOfarm_abovBEL grass_NEW crops_NEW
catttle11code sheep11code
    pigs11code poultry11code (ORDER=DESCENDING) WITH pcnt65to100A
SEXmalprcnt11 tot_livalone11 Qbeldeg
    FT31plushrs NIMDMrank2010 yesUNPcar LLTIyesTOT OCCprcnt51 LFAfarms11
FARMEDpcnt_NEW
  /MODEL farms11code avSOfarm_abovBEL grass_NEW crops_NEW catttle11code
sheep11code pigs11code
    poultry11code pcnt65to100A SEXmalprcnt11 tot_livalone11 Qbeldeg
FT31plushrs NIMDMrank2010 yesUNPcar
    LLTIyesTOT OCCprcnt51 LFAfarms11 FARMEDpcnt_NEW INTERCEPT=YES
OFFSET=NL_popul11
 DISTRIBUTION=NEGBIN(MLE) LINK=LOG
  /CRITERIA METHOD=FISHER(1) SCALE=1 COVB=ROBUST MAXITERATIONS=1000
MAXSTEPHALVING=50
    PCONVERGE=1E-006(ABSOLUTE) SINGULAR=1E-012 ANALYSISTYPE=3(WALD)
CILEVEL=95 CITYPE=WALD
    LIKELIHOOD=FULL
      /EMMEANS CONTROL=NIMDMrank2010(1)
  /MISSING CLASSMISSING=EXCLUDE
  /PRINT CPS DESCRIPTIVES MODELINFO FIT SUMMARY SOLUTION (EXPONENTIATED)
    /SAVE MEANPRED XBPRED COOK DEVIANCERESID.

I am hoping someone on here knows the syntax or point-and-click method to
solve this issue as I have exhausted youtube videos and reading SPSS syntax
books and journals, perhaps someone knows the solution off-hand, thanks in
advance for any advice, feel free to ask any questions, Kel




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