A relation between a between-item multidimensional IRT model and the mixture rasch model

Two generalizations of the Rasch model are compared: the between-item multidimensional model (Adams, Wilson, and Wang, 1997), and the mixture Rasch model (Mislevy & Verhelst, 1990; Rost, 1990). It is shown that the between-item multidimensional model is formally equivalent with a continuous mixture of Rasch models for which, within each class of the mixture, the item parameters are equal to the item parameters of the multidimensional model up to a shift parameter that is specific for the dimension an item belongs to in the multidimensional model. In a simulation study, the relation between both types of models also holds when the number of classes of the mixture is as small as two. The relation is illustrated with a study on verbal aggression. Frank Rijmen was supported by the Fund for Scientific Research Flanders (FWO). This research is also funded by the GOA/2000/02 granted from the KU Leuven. We would like to thank Kristof Vansteelandt for providing the data of the study on verbal aggression.     

因子混合模型:潜在类别分析与因子分析的整合

因子混合模型(FMM)是考虑了群体潜在异质性后的因子分析模型,它将潜在类别分析(LCA)与传统的因子分析(FA)整合在同一框架内,既保留了两种分析技术的优点,同时又展现出独特优势。FMM的应用主要包括描述变量的潜在结构、对被试进行分组以及探测社会称许偏差等。我们建议分别采用FA、LCA与FMM三种模型拟合数据,参考拟合指数和模型可解释性选择最优模型。总结了FMM的分析步骤以及软件使用,并用于探讨大学生社会面子意识的测量模型。未来研究应关注FMM分析过程的简化,继续深化对拟合指数等方面的探讨。     

Bias-corrected estimation of the Rudas–Clogg–Lindsay mixture index of fit

Rudas, Clogg, and Lindsay (1994, J. R Stat Soc. Ser. B, 56, 623) introduced the so-called mixture index of fit, also known as pi-star (π*), for quantifying the goodness of fit of a model. It is the lowest proportion of ‘contamination’ which, if removed from the population or from the sample, makes the fit of the model perfect. The mixture index of fit has been widely used in psychometric studies. We show that the asymptotic confidence limits proposed by Rudas et al. (1994, J. R Stat Soc. Ser. B, 56, 623) as well as the jackknife confidence interval by Dayton ( 2003 , Br. J. Math. Stat. Psychol., 56, 1) perform poorly, and propose a new bias-corrected point estimate, a bootstrap test and confidence limits for pi-star. The proposed confidence limits have coverage probability much closer to the nominal level than the other methods do. We illustrate the usefulness of the proposed method in practice by presenting some practical applications to log-linear models for contingency tables.     

Daily mood patterns and bulimic behaviors in the natural environment

Objective

Negative affect has been purported to play an important role in the etiology and maintenance of bulimic behaviors. The objective of this study was to identify daily mood patterns in the natural environment exhibited by individuals with bulimia nervosa and to examine the relationship between these patterns and bulimic behaviors.

Method

One hundred thirty-three women aged 18-55 meeting DSM-IV criteria for bulimia nervosa were recruited through clinical referrals and community advertisements. Ecological momentary assessment was used to collect multiple ratings of negative affect, binge eating and purging each day for a two-week period using palmtop computers. Latent growth mixture modeling was used to identify daily mood patterns.

Results

Nine distinct daily mood patterns were identified. The highest rates of binge eating and purging episodes occurred on days characterized by stable high negative affect or increasing negative affect over the course of the day.

Conclusions

These findings support the conclusion that negative mood states are intimately tied to bulimic behaviors and may in fact precipitate such behavior.     

On the inhomogeneity of a test compounded of two Rasch homogeneous subscales

Van den Wollenberg stated a theorem specifying the conditions for a test, which is composed of two Rasch homogeneous subscales, as also behaving Rasch homogeneously. In our note, simple numerical counterexamples are given for which this theorem fails.While preparing the final version of this note, Ilse Rop passed away. The first author therefore takes sole responsibility for this final version.     

Does covenant marriage predict latent trajectory groups of newlywed couples?

Covenant marriage is a legally distinct marriage license available in Arizona, Louisiana, and Arkansas in the United States. This study revisited one of the largest longitudinal dyadic studies on covenant versus standard newlywed couples. Using this dataset of 677 different-sex couples, we explored whether being in a covenant marriage could predict how marital satisfaction developed over the first five marital years. We applied the Growth Mixture Modeling (GMM) method to identify groups that differed in their initial marital satisfaction and trajectory. The results revealed three different trajectory groups—one group showing high and stable marital satisfaction, which we named High Stable, and two groups showing declines in marital satisfaction, one being medium and the other one being low in satisfaction at the beginning of the marriage, and we named them Medium Declining and Low Declining respectively. Spouses with lower initial marital satisfaction experienced a faster decline and suffered the highest divorce rate. Actor-Partner Interdependence Model (APIM) analysis revealed that one's group membership was predicted by their partner's membership, suggesting a mutual influence on marital development. Being in a covenant marriage was able to predict husbands' membership as covenant husbands were found to be more likely in the high stable group.     

Bayesian IRT Guessing Models for Partial Guessing Behaviors

According to the recent Nation’s Report Card, 12th-graders failed to produce gains on the 2005 National Assessment of Educational Progress (NAEP) despite earning better grades on average. One possible explanation is that 12th-graders were not motivated taking the NAEP, which is a low-stakes test. We develop three Bayesian IRT mixture models to describe the results from a group of examinees including both nonguessers and partial guessers. The first assumes that the guesser answers questions based on his or her knowledge up to a certain test item, and guesses thereafter. The second model assumes that the guesser answers relatively easy questions based on his or her knowledge and guesses randomly on the remaining items. The third is constructed to describe more general low-motivation behavior. It assumes that the guesser gives less and less effort as he or she proceeds through the test. The models can provide not only consistent estimates of IRT parameters but also estimates of each examinee’s nonguesser/guesser status and degree of guessing behavior. We show results of a simulation study comparing the performance of the three guessing models to the 2PL-IRT model. Finally, an analysis of real data from a low-stakes test administered to university students is presented.     

Bayesian inference for graphical factor analysis models

We generalize factor analysis models by allowing the concentration matrix of the residuals to have nonzero off-diagonal elements. The resulting model is named graphical factor analysis model. Allowing a structure of associations gives information about the correlation left unexplained by the unobserved variables, which can be used both in the confirmatory and exploratory context. We first present a sufficient condition for global identifiability of this class of models with a generic number of factors, thereby extending the results in Stanghellini (1997) and Vicard (2000). We then consider the issue of model comparison and show that fast local computations are possible for this purpose, if the conditional independence graphs on the residuals are restricted to be decomposable and a Bayesian approach is adopted. To achieve this aim, we propose a new reversible jump MCMC method to approximate the posterior probabilities of the considered models. We then study the evolution of political democracy in 75 developing countries based on eight measures of democracy in two different years. We acknowledge support from M.U.R.S.T. of Italy and from the European Science Foundation H.S.S.S. Network. We are grateful to the referees and the Editor for many useful suggestions and comments which led to a substantial improvement of the paper. We also thank Nanny Wermuth for stimulating discussions and Kenneth A. Bollen for kindly providing us with the data-set.