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From |
Hitesh Chandwani <hchandwani.stata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: How to model a positive continuous dependent variable with many zeros? |

Date |
Thu, 2 Jun 2011 11:14:42 -0400 |

Adrian, Do you mean: after > modeling the zeros, model the non-zeros by deleting the zeros from > the data set using the same predictors?...... Basically, yes. The first model will give you the probability of having non-zero durations. This probability can then be multiplied with estimates from the GLM to obtain an unbiased (more conservative) estimate of mean seclusion duration. I do have some references for two-part analyses...however, they all deal with modeling cost data. I will email them to the listserv in a few hours (once i get to my computer). Sent from my iPhone On Wed, Jun 1, 2011 at 2:38 AM, Adriaan Hoogendoorn <aw.hoogendoorn@gmail.com> wrote: > Thank you, Hithesh (and Maarten in a previous post), for your help. > Your help is highly appreciated. > > The situation Maarten described appears exactly to be the case: > Clinic staff members try reducing total seclusion durations (at the > clinic level) by ending seclusions as soon as possible at the risk > of introducing more seclusion episodes. Total seclusion duration > (rated against the total time spent in the clinic) seems the > appropriate quantity to evaluate seclusion policies. We find that > total seclusion durations differ substantially across clinics. The > explanation clinics give for having higher total seclusion durations > than other clinics is that they claim to have “harder” patients, as > Maarten suggested. > > Explaining these differences from patient characteristics (and some > clinic characteristics) is exactly what this study is about. > > Your suggestion of combining the modeled zeros (from a logistic > regression, or from the Poisson as Maarten suggested) with a model for > non-zero duration (from GLM or Survival Analysis) seems very attractive. > However, I have no experience on how to do this. Do you mean: after > modeling the zeros, model the non-zeros by deleting the zeros from > the data set using the same predictors? > > This would provide me with two sets of parameters. Do you think I can > use these two sets of model parameters > to estimate the total seclusion > duration for a given ward with a given set of patients? > > I’ve never seen such a combined model in scientific literature – which > may well be my mistake. Do you have any references how such a combination > was applied and discussed? > > Kind regards, > Adriaan W. Hoogendoorn > GGZ inGeest, Amsterdam > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > -- Hitesh S. Chandwani University of Texas at Austin * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: How to model a positive continuous dependent variable with many zeros?***From:*Steven Samuels <sjsamuels@gmail.com>

**Re: st: How to model a positive continuous dependent variable with many zeros?***From:*Steven Samuels <sjsamuels@gmail.com>

**References**:**Re: st: How to model a positive continuous dependent variable with many zeros?***From:*Adriaan Hoogendoorn <aw.hoogendoorn@gmail.com>

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