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Articles 1 - 9 of 9

Full-Text Articles in Social and Behavioral Sciences

Marginal Structural Models: An Application To Incarceration And Marriage During Young Adulthood, Valerio Bacak, Edward Kennedy Jan 2015

Marginal Structural Models: An Application To Incarceration And Marriage During Young Adulthood, Valerio Bacak, Edward Kennedy

Edward H. Kennedy

Advanced methods for panel data analysis are commonly used in research on family life and relationships, but the fundamental issue of simultaneous time-dependent confounding and mediation has received little attention. In this article the authors introduce inverse-probability-weighted estimation of marginal structural models, an approach to causal analysis that (unlike conventional regression modeling) appropriately adjusts for confounding variables on the causal pathway linking the treatment with the outcome. They discuss the need for marginal structural models in social science research and describe their estimation in detail. Substantively, the authors contribute to the ongoing debate on the effects of incarceration on marriage …

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Generating A Dynamic Synthetic Population – Using An Age-Structured Two-Sex Model For Household Dynamics, Mohammad-Reza Namazi-Rad, Payam Mokhtarian, Pascal Perez Apr 2014

Generating A Dynamic Synthetic Population – Using An Age-Structured Two-Sex Model For Household Dynamics, Mohammad-Reza Namazi-Rad, Payam Mokhtarian, Pascal Perez

Payam Mokhtarian

Generating a reliable computer-simulated synthetic population is necessary for knowledge processing and decision-making analysis in agent-based systems in order to measure, interpret and describe each target area and the human activity patterns within it. In this paper, both synthetic reconstruction (SR) and combinatorial optimisation (CO) techniques are discussed for generating a reliable synthetic population for a certain geographic region (in Australia) using aggregated- and disaggregated-level information available for such an area. A CO algorithm using the quadratic function of population estimators is presented in this paper in order to generate a synthetic population while considering a two-fold nested structure for …

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A Probabilistic Predictive Model For Residential Mobility In Australia, Mohammad-Reza Namazi-Rad, Nagesh Shukla, Albert Munoz, Payam Mokhtarian, Jun Ma Mar 2014

A Probabilistic Predictive Model For Residential Mobility In Australia, Mohammad-Reza Namazi-Rad, Nagesh Shukla, Albert Munoz, Payam Mokhtarian, Jun Ma

Payam Mokhtarian

Household relocation modelling is an integral part of the planning process as residential movements influence the demand for community facilities and services. Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) created the Household, Income and Labour Dynamics in Australia (HILDA) program to collect reliable longitudinal data on family and household dynamics. Socio-demographic information (such as general health situation and well-being, lifestyle changes, residential mobility, income and welfare dynamics, and labour market dynamics) is collected from the sampled individuals and households. The data shows that approximately 17% of Australian households and 13% of couple families in the HILDA sample …

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Relation Of Baseline Systolic Blood Pressure And Long-Term Outcomes In Ambulatory Patients With Chronic Mild To Moderate Heart Failure, Maciej Banach, Vikas Bhatia, Margaret Feller, Marjan Mujib, Ravi Desai, Mustafa Ahmed, Jason Guichard, Inmaculada Aban, Thomas Love, Wilbert Aronow, Michel White, Prakash Deedwania, Gregg Fonarow, Ali Ahmed Jul 2013

Relation Of Baseline Systolic Blood Pressure And Long-Term Outcomes In Ambulatory Patients With Chronic Mild To Moderate Heart Failure, Maciej Banach, Vikas Bhatia, Margaret Feller, Marjan Mujib, Ravi Desai, Mustafa Ahmed, Jason Guichard, Inmaculada Aban, Thomas Love, Wilbert Aronow, Michel White, Prakash Deedwania, Gregg Fonarow, Ali Ahmed

Ravi V Desai MD

No abstract provided.

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Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans Dec 2012

Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans

Lonnie K. Stevans

The econometric literature on unit roots took off after the publication of the paper by Nelson and Plosser (1982) that argued that most macroeconomic series have unit roots and that this is important for the analysis of macroeconomic policy. Yule (1926) suggested that regressions based on trending time series data can be spurious. This problem of spurious correlation was further pursued by Granger and Newbold (1974) and this also led to the development of the concept of cointegration (lack of cointegration implies spurious regression). The pathbreaking paper by Granger (1981), first presented at a conference at the University of Florida …

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Statistical Methods Used In Gifted Education Journals, 2006-2010, Russell Warne, Maria Lazo, Tami Ramos, Nicola Ritter Jun 2012

Statistical Methods Used In Gifted Education Journals, 2006-2010, Russell Warne, Maria Lazo, Tami Ramos, Nicola Ritter

Russell T Warne

This article describes the statistical methods used in quantitative and mixed methods articles between 2006 and 2010 in five gifted education research journals. Results indicate that the most commonly used statistical methods are means (85.9% of articles), standard deviations (77.8%), Pearson’s r (47.8%), χ2 (32.2%), ANOVA (30.7%), t tests (30.0%), and MANOVA (23.0%). Approximately half (53.3%) of the articles included reliability reports for the data at hand; Cronbach’s alpha was the most commonly reported measure of reliability (41.5%). Some discussions of best statistical practice and implications for the field of gifted education are included.

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Managing Clustered Data Using Hierarchical Linear Modeling, Russell Warne Apr 2012

Managing Clustered Data Using Hierarchical Linear Modeling, Russell Warne

Russell T Warne

Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence assumption and lead to correct analysis of data, yet it is rarely used in nutrition research. The purpose of this viewpoint is to illustrate the benefits of hierarchical linear modeling within a nutrition research context.

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Beyond Multiple Regression: Using Commonality Analysis To Better Understand R2 Results, Russell Warne Sep 2011

Beyond Multiple Regression: Using Commonality Analysis To Better Understand R2 Results, Russell Warne

Russell T Warne

Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated independent variables. Commonality analysis—heretofore rarely used in gifted education research—is a statistical method that partitions the explained variance of a dependent variable into nonoverlapping parts according to the independent variable(s) that are related to each portion. This Methodological Brief includes an example of commonality analysis and equations for researchers who wish to conduct their …

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The Journey To Safety: Conflict-Driven Migration Flows In Colombia, Gianfranco Piras, Nancy Lozano-Gracia, Geoffrey Hewings, Ana Maria Ibanez Dec 2009

The Journey To Safety: Conflict-Driven Migration Flows In Colombia, Gianfranco Piras, Nancy Lozano-Gracia, Geoffrey Hewings, Ana Maria Ibanez

Gianfranco Piras

No abstract provided.

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