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Articles 1 - 12 of 12
Full-Text Articles in Statistical Models
Risk, Odds, And Their Ratios, Joseph Hilbe
Risk, Odds, And Their Ratios, Joseph Hilbe
Joseph M Hilbe
A brief monograph explaining the meaning of the terms, risk, risk ratio, odds, and odds ratio and how to calculate each, together with standard errors and confidence intervals. Stata code is provided showing how all of the terms can be calculated by hand, as well as by using logistic and Poisson models.
Negative Binomial Regression Extensions, Joseph Hilbe
Negative Binomial Regression Extensions, Joseph Hilbe
Joseph M Hilbe
Negative Binomial Regression Extensions is an e-book extension of Negative Binomial Regression, 2nd edition, with added R and Stata code, and SAS macros all related to count models.
Suppliment To Logistic Regression Models, Joseph Hilbe
Suppliment To Logistic Regression Models, Joseph Hilbe
Joseph M Hilbe
No abstract provided.
Basic R Matrix Operations, Joseph Hilbe
Using R To Create Synthetic Discrete Response Regression Models, Joseph Hilbe
Using R To Create Synthetic Discrete Response Regression Models, Joseph Hilbe
Joseph M Hilbe
The creation of synthetic models allows a researcher to better understand models as well as the bias that can occur when the assumptions upon which a model is based is violated. This article provides R code that can be used or amended to create a variety of discrete response regression models.
U.S. Cultural Involvement And Its Association With Co-Occurring Substance Abuse And Sexual Risk Behaviors Among Youth In The Dominican Republic, Elián P. Cabrera-Nguyen, Juan B. Peña
U.S. Cultural Involvement And Its Association With Co-Occurring Substance Abuse And Sexual Risk Behaviors Among Youth In The Dominican Republic, Elián P. Cabrera-Nguyen, Juan B. Peña
Elián P. Cabrera-Nguyen
We examined the relationship of US cultural involvement with substance abuse and sexual risk behavior profiles from our nationally representative sample of public high school students in the Dominican Republic. Using a novel methodological approach to control for selection bias, we examined explanations for the so-called Latino or Hispanic immigrant paradox. A latent class regression analysis with manifest and latent covariates found that US cultural involvement indicators were independent and robust predictors of increased risk of co-ocurring substance abuse and sexual risk behaviors. Implications for prevention efforts targeting risk behaviors among Latino/a adolescents in the US and abroad are considered.
Nbr2 Stata Ado-Do Files, Joseph Hilbe
Multilevel Latent Class Models With Dirichlet Mixing Distribution, Chong-Zhi Di, Karen Bandeen-Roche
Multilevel Latent Class Models With Dirichlet Mixing Distribution, Chong-Zhi Di, Karen Bandeen-Roche
Chongzhi Di
Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social sciences and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we consider multilevel latent class models, in which sub-population mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the Expectation-Maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when …
Likelihood Ratio Testing For Admixture Models With Application To Genetic Linkage Analysis, Chong-Zhi Di, Kung-Yee Liang
Likelihood Ratio Testing For Admixture Models With Application To Genetic Linkage Analysis, Chong-Zhi Di, Kung-Yee Liang
Chongzhi Di
We consider likelihood ratio tests (LRT) and their modifications for homogeneity in admixture models. The admixture model is a special case of two component mixture model, where one component is indexed by an unknown parameter while the parameter value for the other component is known. It has been widely used in genetic linkage analysis under heterogeneity, in which the kernel distribution is binomial. For such models, it is long recognized that testing for homogeneity is nonstandard and the LRT statistic does not converge to a conventional 2 distribution. In this paper, we investigate the asymptotic behavior of the LRT for …
Comparing Paired Vs. Non-Paired Statistical Methods Of Analyses When Making Inferences About Absolute Risk Reductions In Propensity-Score Matched Samples., Peter C. Austin
Peter Austin
Propensity-score matching allows one to reduce the effects of treatment-selection bias or confounding when estimating the effects of treatments when using observational data. Some authors have suggested that methods of inference appropriate for independent samples can be used for assessing the statistical significance of treatment effects when using propensity-score matching. Indeed, many authors in the applied medical literature use methods for independent samples when making inferences about treatment effects using propensity-score matched samples. Dichotomous outcomes are common in healthcare research. In this study, we used Monte Carlo simulations to examine the effect on inferences about risk differences (or absolute risk …
Optimal Caliper Widths For Propensity-Score Matching When Estimating Differences In Means And Differences In Proportions In Observational Studies., Peter C. Austin
Optimal Caliper Widths For Propensity-Score Matching When Estimating Differences In Means And Differences In Proportions In Observational Studies., Peter C. Austin
Peter Austin
In a study comparing the effects of two treatments, the propensity score is the probability of assignment to one treatment conditional on a subject's measured baseline covariates. Propensity-score matching is increasingly being used to estimate the effects of exposures using observational data. In the most common implementation of propensity-score matching, pairs of treated and untreated subjects are formed whose propensity scores differ by at most a pre-specified amount (the caliper width). There has been a little research into the optimal caliper width. We conducted an extensive series of Monte Carlo simulations to determine the optimal caliper width for estimating differences …
A Tutorial And Case Study In Propensity Score Analysis: An Application To Estimating The Effect Of In-Hospital Smoking Cessation Counseling On Mortality, Peter C. Austin
A Tutorial And Case Study In Propensity Score Analysis: An Application To Estimating The Effect Of In-Hospital Smoking Cessation Counseling On Mortality, Peter C. Austin
Peter Austin
Propensity score methods allow investigators to estimate causal treatment effects using observational or nonrandomized data. In this article we provide a practical illustration of the appropriate steps in conducting propensity score analyses. For illustrative purposes, we use a sample of current smokers who were discharged alive after being hospitalized with a diagnosis of acute myocardial infarction. The exposure of interest was receipt of smoking cessation counseling prior to hospital discharge and the outcome was mortality with 3 years of hospital discharge. We illustrate the following concepts: first, how to specify the propensity score model; second, how to match treated and …