Chris posted “Walmart and the ASA” to the orgtheory blog. The piece is about the recent ASA Amicus Brief which supports the use of social framework analysis by social scientists who act as expert witnesses in, and whose conclusions can support class certification of, large class action discrimination litigation cases. This issue is generating a lot of debate, on scatterplot as well as orgtheory, the outcome of which might have important implications for the role of social scientists in legal processes, such as the current Walmart case [more on the case here 1, 2, 3] to be decided on this summer. Discussion on the blog has also incorporated other issues relating to the mission and role of ASA.

## An Extended Model Comparison Framework for Covariance and Mean Structure Models, Accommodating Multiple Groups and Latent Mixtures

May 19, 2011Levy, R., & Hancock, G. (2011). An Extended Model Comparison Framework for Covariance and Mean Structure Models, Accommodating Multiple Groups and Latent Mixtures Sociological Methods & Research, 40 (2), 256-278 DOI: 10.1177/0049124111404819

Roy Levy, Arizona State University, Tempe, AZ, USA, roy.levy@asu.edu

## Measurement Equivalence of Ordinal Items: A Comparison of Factor Analytic, Item Response Theory, and Latent Class Approaches

May 19, 2011Kankaras, M., Vermunt, J., & Moors, G. (2011). Measurement Equivalence of Ordinal Items: A Comparison of Factor Analytic, Item Response Theory, and Latent Class Approaches Sociological Methods & Research, 40 (2), 279-310 DOI: 10.1177/0049124111405301

Miloš Kankaraš, Tilburg University, Tilburg, The Netherlands, m.kankaras@uvt.nl

## Multiple Auxiliary Variables in Nonresponse Adjustment

May 19, 2011Kreuter, F., & Olson, K. (2011). Multiple Auxiliary Variables in Nonresponse Adjustment Sociological Methods & Research, 40 (2), 311-332 DOI: 10.1177/0049124111400042

Frauke Kreuter, University of Maryland, College Park, USA and Institute for Employment Research, Nuremberg, Germany, fkreuter@survey.umd.edu

## When Change Matters: An Analysis of Survey Interaction in Dependent Interviewing on the British Household Panel Study

May 19, 2011Uhrig, S., & Sala, E. (2011). When Change Matters: An Analysis of Survey Interaction in Dependent Interviewing on the British Household Panel Study Sociological Methods & Research, 40 (2), 333-366 DOI: 10.1177/0049124111404816

SC Noah Uhrig, University of Essex, United Kingdom, scnuhrig@essex.ac.uk

## Group-based Trajectory Modeling Extended to Account for Nonrandom Participant Attrition

May 19, 2011Haviland, A., Jones, B., & Nagin, D. (2011). Group-based Trajectory Modeling Extended to Account for Nonrandom Participant Attrition Sociological Methods & Research, 40 (2), 367-390 DOI: 10.1177/0049124111400041

Daniel S. Nagin, Carnegie Mellon University, Pittsburgh, PA, USA, dn03@andrew.cmu.edu

## Assessing the Robustness of Crisp-set and Fuzzy-set QCA Results

May 19, 2011Skaaning, S. (2011). Assessing the Robustness of Crisp-set and Fuzzy-set QCA Results Sociological Methods & Research DOI: 10.1177/0049124111404818

Svend-Erik Skaaning, Aarhus University, Aarhus, Denmark, Skaaning@ps.au.dk

## SMR 40.1 TOC

January 12, 2011Table of Contents for *Sociological Methods & Research* 40.1 (February 2011). With this issue, SMR begins its 40th year!

## Nonparametric Tests of Panel Conditioning and Attrition Bias in Panel Surveys

January 12, 2011Das, M., Toepoel, V., & van Soest, A. (2011). **Nonparametric Tests of Panel Conditioning and Attrition Bias in Panel Surveys,** Sociological Methods & Research, 40 (1), 32-56 DOI: 10.1177/0049124110390765, view abstract.

## Two Algorithms for Relaxed Structural Balance Partitioning: Linking Theory, Models, and Data to Understand Social Network Phenomena

January 12, 2011Brusco, M., Doreian, P., Mrvar, A., & Steinley, D. (2010). **Two Algorithms for Relaxed Structural Balance Partitioning: Linking Theory, Models, and Data to Understand Social Network Phenomena,** Sociological Methods & Research, 40 (1), 57-87 DOI: 10.1177/0049124110384947, view abstract.

## The Effects of Asking Filter Questions in Interleafed Versus Grouped Format

January 12, 2011Kreuter, F., McCulloch, S., Presser, S., & Tourangeau, R. (2011). **The Effects of Asking Filter Questions in Interleafed Versus Grouped Format **Sociological Methods & Research, 40 (1), 88-104 DOI: 10.1177/0049124110392342, view abstract.

## Estimating Propensity Adjustments for Volunteer Web Surveys

January 12, 2011Valliant, R., & Dever, J. (2011). **Estimating Propensity Adjustments for Volunteer Web Surveys** Sociological Methods & Research, 40 (1), 105-137 DOI: 10.1177/0049124110392533, view abstract.

## Multiple Sources of Nonobservation Error in Telephone Surveys: Coverage and Nonresponse

January 12, 2011Peytchev, A., Carley-Baxter, L., & Black, M. (2011). **Multiple Sources of Nonobservation Error in Telephone Surveys: Coverage and Nonresponse** Sociological Methods & Research, 40 (1), 138-168 DOI: 10.1177/0049124110392547, view abstract.

## Sensitive Questions in Online Surveys: Experimental Results for the Randomized Response Technique (RRT) and the Unmatched Count Technique (UCT)

January 12, 2011Coutts, E., & Jann, B. (2011). **Sensitive Questions in Online Surveys: Experimental Results for the Randomized Response Technique (RRT) and the Unmatched Count Technique (UCT)** Sociological Methods & Research, 40 (1), 169-193 DOI: 10.1177/0049124110390768, view abstract.

## SMR 39.2 TOC

November 12, 2010## Model Identification and Computer Algebra

November 12, 2010Kenneth A. Bollen and Shawn Bauldry, **Model Identification and Computer Algebra**, Sociological Methods & Research 2010 39: 127-156.

Multiequation models that contain observed or latent variables are common in the social sciences. To determine whether unique parameter values exist for such models, one needs to assess model identification. Read the rest of this entry »

## Assessing Group Differences in Estimated Baseline Survivor Functions From Cox Proportional Hazards Models

November 12, 2010Daniel A. Powers, **Assessing Group Differences in Estimated Baseline Survivor Functions From Cox Proportional Hazards Models**, Sociological Methods & Research 2010 39: 157-187.

The author discusses the general problem of evaluating differences in adjusted survivor functions and develops a heuristic approach to generate the expected events that would occur Read the rest of this entry »

## Proportional Reduction of Prediction Error in Cross-Classified Random Effects Models

November 12, 2010Wen Luo and Oi-Man Kwok, **Proportional Reduction of Prediction Error in Cross-Classified Random Effects Models**, Sociological Methods & Research 2010 39: 188-205.

As an extension of hierarchical linear models (HLMs), cross-classified random effects models (CCREMs) are used for analyzing multilevel data that do not have strictly Read the rest of this entry »

## An Alternative to the Bar-Lev, Bobovitch, and Boukai Randomized Response Model

November 12, 2010Oluseun Odumade and Sarjinder Singh, **An Alternative to the Bar-Lev, Bobovitch, and Boukai Randomized Response Model**, Sociological Methods & Research 2010 39: 206-221.

In this article, an alternative randomized response model is proposed. The proposed model is found to be more efficient than the randomized response model studied by Bar-Lev, Bobovitch, and Boukai (2004). Read the rest of this entry »

## Latent Markov Model for Analyzing Temporal Configuration for Violence Profiles and Trajectories in a Sample of Batterers

November 12, 2010Edward H. Ip, Alison Snow Jones, D. Alex Heckert, Qiang Zhang and Edward D. Gondolf, **Latent Markov Model for Analyzing Temporal Configuration for Violence Profiles and Trajectories in a Sample of Batterers**, Sociological Methods & Research 2010 39: 222-255.

In this article, the authors demonstrate the utility of an extended latent Markov model for analyzing temporal configurations in the behaviors of a sample of 550 domestic violence batterers. Read the rest of this entry »

## A Cautionary Note on the Use of Matching to Estimate Causal Effects: An Empirical Example Comparing Matching Estimates to an Experimental Benchmark

November 12, 2010Kevin Arceneaux, Alan S. Gerber, and Donald P. Green, **A Cautionary Note on the Use of Matching to Estimate Causal Effects: An Empirical Example Comparing Matching Estimates to an Experimental Benchmark**, Sociological Methods & Research 2010 39: 256-282.

In recent years, social scientists have increasingly turned to matching as a method for drawing causal inferences from observational data. Matching compares those who receive a treatment to those with similar Read the rest of this entry »

## A Note on a Simple and Practical Randomized Response Framework for Eliciting Sensitive Dichotomous and Quantitative Information

November 12, 2010Carel F. W. Peeters, Gerty J. L. M. Lensvelt-Mulders and Karin Lasthuizen, A Note on a Simple and Practical Randomized Response Framework for Eliciting Sensitive Dichotomous and Quantitative Information, Sociological Methods & Research 2010 39: 283-296.

Many issues of interest to social scientists and policy makers are of a sensitive nature in the sense that they are intrusive, stigmatizing, or incriminating to the respondent. Read the rest of this entry »

## Mixture Models for Ordinal Data

August 12, 2010Richard Breen and Ruud Luijkx, Mixture Models for Ordinal DataSociological Methods & Research 2010 39: 3-24.

Cumulative probability models are widely used for the analysis of ordinal data. In this article the authors propose cumulative probability mixture models that allow the assumptions of the cumulative probability model Read the rest of this entry »

## Analysis of a Two-Level Structural Equation Model With Missing Data

August 12, 2010Wai-Yin Poon and Hai-Bin Wang, **Analysis of a Two-Level Structural Equation Model With Missing Data**, Sociological Methods & Research 2010 39: 25-55.

Structural equation models are widely used to model relationships among latent unobservable constructs and observable variables. In some studies, the data set used for analysis is comprised of observations that are drawn Read the rest of this entry »

## Cross-Survey Analysis to Estimate Low-Incidence Religious Groups

August 12, 2010Elizabeth Tighe, David Livert, Melissa Barnett, and Leonard Saxe, **Cross-Survey Analysis to Estimate Low-Incidence Religious Groups**, Sociological Methods & Research 2010 39: 56-82.

## Fitting Log-Linear Models to Contingency Tables From Surveys With Complex Sampling Designs: An Investigation of the Clogg-Eliason Approach

August 12, 2010**Fitting Log-Linear Models to Contingency Tables From Surveys With Complex Sampling Designs: An Investigation of the Clogg-Eliason Approach**, Sociological Methods & Research 2010 39: 83-108.

## Multiple Informant Methodology: A Critical Review and Recommendations

June 17, 2010The value of multiple informant methodology for improving the^{ }validity in determining organizational properties has been increasinglyrecognized. However, the majority of empirical research Read the rest of this entry »

## Decomposing the Change in the Wage Gap Between White and Black Men Over Time, 1980-2005: An Extension of the Blinder-Oaxaca Decomposition Method

June 17, 2010This article extends the Blinder—Oaxaca decomposition^{ }method to the decomposition of changes in the wage gap between^{ }white and black men over time. The previously implemented technique,^{ }in which the contributions of two decomposition components areestimated by Read the rest of this entry »

## New Developments in Sequence Analysis

May 13, 2010Christian Brzinsky-Fay and Ulrich Kohler: New Developments in Sequence Analysis, Sociological Methods Research 2010 38: 359-364.

Sequence analysis was originally invented by biologists with the aim of comparing DNA sequences in order to find out to what extent two DNA strands are homologous Read the rest of this entry »

## Optimal Matching Analysis and Life-Course Data: The Importance of Duration

May 13, 2010Brendan Halpin: Optimal Matching Analysis and Life-Course Data: The Importance of Duration, Sociological Methods Research 2010 38: 365-388.

The optimal matching (OM) algorithm is widely used for sequence analysis insociology. It has a natural interpretation for discrete-time sequences but isalso widely used for life-history data, which are Read the rest of this entry »

## Complexity of Categorical Time Series

May 13, 2010Cees H. Elzinga: Complexity of Categorical Time Series, Sociological Methods Research 2010 38: 463-481.

Categorical time series, covering comparable time spans, are often quite different in a number of aspects: the number of distinct states, the number of transitions, and the distribution of durations Read the rest of this entry »

## My Brilliant Career: Characterizing the Early Labor Market Trajectories of British Women From Generation X

May 13, 2010Michael Anyadike-Danes and Duncan McVicar: My Brilliant Career: Characterizing the Early Labor Market Trajectories of British Women From Generation X Sociological Methods Research 2010 38: 482-512.

This article uses longitudinal data from the British Cohort Study to examinethe early labor market trajectories Read the rest of this entry »

## Special Issue on Sequence Analysis

April 21, 2010The entire February issue of SMR, a special issue on Sequence Analysis, has been posted to the blog. Users can download a PDF of each article free of charge. The special issue has been edited by Christian Brzinsky-Fay and Ulrich Kohler of the Social Science Research Center, Berlin (Wissenschaftszentrum Berlin für Sozialforschung), Read the rest of this entry »

## SMR Welcomes New Editorial Board Members

April 21, 2010SMR has added six new members to the Editorial Board for 2010.

These 6 scholars took on a lot of reviewing for SMR in recent years. Please join us in welcoming Read the rest of this entry »

## SMR Blog Launch: Registration + Setup

April 21, 2010The SMR Blog officially launches on May 19th.

All SMR citations (with abstracts) since 2005 have been posted to the blog. Read the rest of this entry »

## Book Review: Regression Analysis: A Constructive Critique. Advanced Quantitative Techniques in the Social Sciences Series 11, by Richard A. Berk

February 7, 2010## Book Review: Regression With Social Data: Modeling Continuous and Limited Response Variables, by Alfred DeMaris

February 7, 2010## Question Order and Interviewer Effects in CATI Scale-up Surveys

February 7, 2010**Silvia Snidero, Federica Zobec, Paola Berchialla, Roberto Corradetti, and Dario Gregori Question Order and Interviewer Effects in CATI Scale-up Surveys**** Sociological Methods & Research 2009 38: 287-305.**

The scale-up estimator is a network-based estimator for the^{ }size of hidden or hard to count subpopulations. Several issues^{ }arise in the public health context when the aim is the estimation^{ }of injuries occurring in a certain population, Read the rest of this entry »

## A Coefficient of Association Between Categorical Variables With Partial or Tentative Ordering of Categories

February 7, 2010**Volkert Siersma and Svend Kreiner: A Coefficient of Association Between Categorical Variables With Partial or Tentative Ordering of Categories**** Sociological Methods & Research 2009 38: 265-286.**

Goodman and Kruskal’s coefficient measuring monotone^{ }association and its partial variants are useful for the analysis^{ }of multiway contingency tables containing ordinal variables.^{ }When the categories of a variable are only partly ordered Read the rest of this entry »

## Is Optimal Matching Suboptimal?

February 7, 2010**Matissa Hollister Is Optimal Matching Suboptimal?**** Sociological Methods & Research 2009 38: 235-264.**

Optimal matching (OM) is a method for measuring the similarity^{ }between pairs of sequences (e.g., work histories). This article^{ }discusses two problems with optimal matching. First, the authoridentifies a flaw in OM ‘‘indel costs’’^{ }and proposes a solution Read the rest of this entry »

## How Much Does It Cost?: Optimization of Costs in Sequence Analysis of Social Science Data

February 7, 2010**Jacques-Antoine Gauthier, Eric D. Widmer, Philipp Bucher, and Cédric Notredame How Much Does It Cost?: Optimization of Costs in Sequence Analysis of Social Science Data**** Sociological Methods & Research 2009 38: 197-231.**

One major methodological problem in analysis of sequence data^{ }is the determination of costs from which distances between sequences^{ }are derived. Although this problem is currently not optimally dealt with in the social sciences, it has Read the rest of this entry »

## Robustness of Group-Based Models for Longitudinal Count Data

February 7, 2010**David L. Weakliem and Bradley R. Entner Wright Robustness of Group-Based Models for Longitudinal Count Data**** Sociological Methods & Research 2009 38: 147-170.**

In recent years, there have been efforts to develop latent class^{ }models for trajectories. The semiparametric mixed Poisson regression^{ }(SMPR) model has been used in many empirical studies, but there^{ }have been few attempts to evaluate the robustness of the estimates Read the rest of this entry »

## Goodness-of-Fit Tests and Descriptive Measures in Fuzzy-Set Analysis

February 7, 2010**Scott R. Eliason and Robin Stryker Goodness-of-Fit Tests and Descriptive Measures in Fuzzy-Set Analysis**** Sociological Methods & Research 2009 38: 102-146.**

In this article the authors develop goodness-of-fit tests for^{ }fuzzy-set analyses to formally assess the fit between empirical^{ }information and various causal hypotheses while accounting formeasurement error in membership scores. These goodness-of-fit^{ }tests, Read the rest of this entry »