SPSSX Discussion - Re: Negative binomial v. ZINB: Plot probabilities

Re: Negative binomial v. ZINB: Plot probabilities

Posted by Jon Peck on Nov 08, 2018; 7:51pm
URL: http://spssx-discussion.165.s1.nabble.com/Negative-binomial-v-ZINB-Plot-probabilities-tp5736964p5736969.html

Where are you stuck? Predicting with the STATS ZEROINFL model gives you a dataset containing the predicted values and probabilities. If you merge this into the main dataset, you could do a scatterplot of the two sets of results.

On Thu, Nov 8, 2018 at 8:05 AM Ives, Melissa L <[hidden email]> wrote:

Good morning SPSS gurus!

We have an analysis using a propensity score (likely to be in inEMPS) split into quintiles to compare inEMP=1 to inEMPS=0.

We have run a Negative Binomial due to over-dispersion—but a question has been raised about why not a zero-inflated NB.

I have run both (using LOGISTIC and STATS_ZEROINFL) both overall and separately (split file for NB/select if in quintile for ZINB).

Now the question is: Which is better? Since the AIC is only slightly lower for ZINB (around 30/>18000), I’ve been asked to

“plot fitted probabilities of the observed data under the zero-inﬂated and the non-zero inﬂated model against each other”

I hope someone can help me with the (best) way to get these plots (within quintile) for NB and ZINB.

This is my first attempt at ZINB.

Here is the syntax I used for both

*** ZERO INFLATED NEGATIVE BINOMIAL USING nBH_EDPre (NUMBER of PRE ED visits).

STATS ZEROINFL MODELSOURCE=ESTIMATE DEPENDENT=nBH_EDPOST COUNTMODEL=inEMPS LR3pred nBH_EDPRE

SAMEREGRESSORS=YES

  COUNTDIST=NEGBIN ZEROLINK=LOGIT

/OPTIONS STARTVALUES=GENLIN OPTMETHOD=BFGS MAXITER=1000 TOL=0.0000000001

/SAVE DATASET=ZI_NB_n

  ID=CID

WORKSPACEACTION=CLEAR.

**************************.

**** With N Pre.

**************************.

LOGISTIC REGRESSION VARIABLES AnyBH_EDPOST

/METHOD=ENTER inEMPS

  /METHOD=ENTER inEMPS nBH_EDPRE

  /PRINT=GOODFIT CI(95)

/CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).

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

Melissa Ives

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Jon K Peck
[hidden email]

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