In mental health services research, analyzing service utilization data often poses serious problems, given the presence of substantially skewed data distributions. This article presents a non-technical introduction to statistical methods specifically designed to handle the complexly distributed datasets that represent mental health service use, including Poisson, negative binomial, zero-inflated, and zero-truncated regression models. A flowchart is provided to assist the investigator in selecting the most appropriate method. Finally, a dataset of mental health service use reported by medical patients is described, and a comparison of results across several different statistical methods is presented. Implications of matching data analytic techniques appropriately with the often complexly distributed datasets of mental health services utilization variables are discussed.
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%0 Journal Article
%1 Elhai2008
%A Elhai, Jon D
%A Calhoun, Patrick S
%A Ford, Julian D
%D 2008
%J Psychiatry research
%K CommunityMentalHealthServices CommunityMentalHealthServices:statistics&num CommunityMentalHealthServices:utilization HealthCareCosts HealthCareCosts:statistics&numericaldata HealthServicesNeedsandDemand HealthServicesNeedsandDemand:economics HealthServicesNeedsandDemand:statistics&num HealthServicesResearch HealthServicesResearch:methods HealthServicesResearch:statistics&numericald Humans MentalDisorders MentalDisorders:epidemiology MentalDisorders:psychology MentalHealthServices MentalHealthServices:statistics&numericaldat MentalHealthServices:supply&distribution MentalHealthServices:utilization Models PoissonDistribution RegressionAnalysis Statistical UtilizationReview UtilizationReview:methods UtilizationReview:statistics&numericaldata
%N 2
%P 129-36
%R 10.1016/j.psychres.2007.07.003
%T Statistical procedures for analyzing mental health services data.
%U http://www.sciencedirect.com/science/article/B6TBV-4SW8588-1/2/bbf3354cd206147845f63e056f5a070f http://www.ncbi.nlm.nih.gov/pubmed/18585790
%V 160
%X In mental health services research, analyzing service utilization data often poses serious problems, given the presence of substantially skewed data distributions. This article presents a non-technical introduction to statistical methods specifically designed to handle the complexly distributed datasets that represent mental health service use, including Poisson, negative binomial, zero-inflated, and zero-truncated regression models. A flowchart is provided to assist the investigator in selecting the most appropriate method. Finally, a dataset of mental health service use reported by medical patients is described, and a comparison of results across several different statistical methods is presented. Implications of matching data analytic techniques appropriately with the often complexly distributed datasets of mental health services utilization variables are discussed.
%@ 0165-1781
@article{Elhai2008,
abstract = {In mental health services research, analyzing service utilization data often poses serious problems, given the presence of substantially skewed data distributions. This article presents a non-technical introduction to statistical methods specifically designed to handle the complexly distributed datasets that represent mental health service use, including Poisson, negative binomial, zero-inflated, and zero-truncated regression models. A flowchart is provided to assist the investigator in selecting the most appropriate method. Finally, a dataset of mental health service use reported by medical patients is described, and a comparison of results across several different statistical methods is presented. Implications of matching data analytic techniques appropriately with the often complexly distributed datasets of mental health services utilization variables are discussed.},
added-at = {2023-02-03T11:44:35.000+0100},
author = {Elhai, Jon D and Calhoun, Patrick S and Ford, Julian D},
biburl = {https://www.bibsonomy.org/bibtex/201299c23fa78438d0e1c021a38c32a97/jepcastel},
doi = {10.1016/j.psychres.2007.07.003},
interhash = {3111670b842158f18975be32608c24bd},
intrahash = {01299c23fa78438d0e1c021a38c32a97},
isbn = {0165-1781},
issn = {0165-1781},
journal = {Psychiatry research},
keywords = {CommunityMentalHealthServices CommunityMentalHealthServices:statistics&num CommunityMentalHealthServices:utilization HealthCareCosts HealthCareCosts:statistics&numericaldata HealthServicesNeedsandDemand HealthServicesNeedsandDemand:economics HealthServicesNeedsandDemand:statistics&num HealthServicesResearch HealthServicesResearch:methods HealthServicesResearch:statistics&numericald Humans MentalDisorders MentalDisorders:epidemiology MentalDisorders:psychology MentalHealthServices MentalHealthServices:statistics&numericaldat MentalHealthServices:supply&distribution MentalHealthServices:utilization Models PoissonDistribution RegressionAnalysis Statistical UtilizationReview UtilizationReview:methods UtilizationReview:statistics&numericaldata},
month = {8},
note = 5121,
number = 2,
pages = {129-36},
pmid = {18585790},
timestamp = {2023-02-03T11:44:35.000+0100},
title = {Statistical procedures for analyzing mental health services data.},
url = {http://www.sciencedirect.com/science/article/B6TBV-4SW8588-1/2/bbf3354cd206147845f63e056f5a070f http://www.ncbi.nlm.nih.gov/pubmed/18585790},
volume = 160,
year = 2008
}