1 Mixture Model and Bayesian Model Interpretations Combining Equations 2.1 and 2.2 (Main Text), we can consider the empirical-Bayes hierarchical model as a mixed model with both fixed and random effects in the frequentist setting as given by: logit(pmi) = αm + ZmγXmi +Xmiτ tmm, where ZmγXmi would be considered a fixed effect and Xmiτ tmm a random effect. Alternatively, this model may be viewed ...

This paper tests pair-wise causal relationships between uncertainty, returns and investment using unbalanced panel data of the 13 insurance companies listed in the KSE for the period from 1996 to 2008. Volatility of returns from the daily stock was measured using the GARCH (p, q) for appropriate values of p and q. The study applied panel data models in the lines of common constants, fixed effec...

Correlated data are fairly common in health and social sciences. For example, clustered data arise when subjects are nested in clusters such as classrooms, hospitals, and neighborhoods; while longitudinal data result from multiple measures for the same subject over long period of time; whereas repeated measures data are involved in multiple measurements for the same subject over time or other d...

In panel data, individuals (persons, firms, cities, ... ) are observed at several points in time (days, years, before and after treatment, ...). This handout focuses on panels with relatively few time periods (small T ) and many individuals (large N). This handout introduces the two basic models for the analysis of panel data, the fixed effects model and the random effects model, and presents c...

The objective of meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence base for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research significantly changed over time and this can impair the results and conclusions of meta-analysis. A number of sequential method...

The main objective of this paper is to provide experimental designs for the estimation of fixed effects and two variance components, in the presence of nested random effects. Random nested factors arise from quantity designations such as lot or batch, and from sampling and measurement procedures. We introduce a general class of designs for mixed-effects models with random nested factors, called...

This article introduces a new class of experimental designs, called split factorials, which allow for the estimation of both response surface effects (fixed effects of crossed factors) and variance components arising from nested random effects. With an economical run size, split factorials provide flexibility in dividing the degrees of freedom among the different estimations. For a split factor...

What Do Social Scientists Know About the Benefits of Marriage? A Review of Quantitative Methodologies This study critically reviews quantitative methods that have been employed and evidence that has been gathered to assess the benefits of marriage and consequences of other family structures. The study begins by describing theoretical models of the determinants of different well-being outcomes a...

This paper focuses on the role of remittances on financial expectations in Albania using longitudinal data covering the period 2002-2004. To study the dynamics of income satisfaction at the household level, we use subjective data on past, current and future financial situations and estimate random and fixed effect ordered Probit models. We find that households are more optimistic about the futu...

This paper compares the impacts of SARS and human deaths arising from Avian Flu on international tourist arrivals to Asia. The effects of SARS and human deaths from Avian Flu will be compared directly according to human deaths. The nature of the short run and long run relationship is examined empirically by estimating a static line fixed effect model and a difference transformation dynamic mode...