Vol. 13, No. 1 Spring 2012

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Formulating Latent Growth Using an Explanatory Item Response Model Approach

Mark Wilson, Xiaohui Zheng, and Leah McGuire

Abstract

In this paper, we present a way to extend the Hierarchical Generalized Linear Model (HGLM; Kamata (2001), Raudenbush (1995)) to include the many forms of measurement models available under the formulation known as the Random Coefficients Multinomial Logit (MRCML) Model (Adams, Wilson and Wang, 1997), and apply that to growth modeling. First, we review two different traditions in modeling growth studies: the first is based in the hierarchical linear modeling (HLM) tradition, and the second, which is the topic of this paper, is rooted in the Rasch measurement tradition—this is the linear Latent Growth Item Response Model (LG-IRM). Going beyond the linear case, the LG-IRM approach allows us to considerably extend the range of models available in the HLM tradition to incorporate several of the extensions of IRT models that are used in creating explanatory item response models (EIRM; De Boeck and Wilson, 2004). We next present a number of extensions—including polynomial growth modeling, differential item functioning (DIF) effects, growth functions that can be approximated by polynomial expressions, provision for polytomous responses, person and item covariates (and time varying covariates), and multiple dimensions of growth. We provide two empirical examples to illustrate several of the models, using the ConQuest software (Wu, Adams, Wilson and Haldane, 2008) to carry out the analyses. We also provide several simulations to investigate the success of the estimation procedures.

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Using the Mixed Rasch Model to Analyze Data from the Beliefs and Attitudes About Memory Survey

Everett V. Smith, Jr., Yuping Ying, and Scott W. Brown

Abstract

In this study, we used the Mixed Rasch Model (MRM) to analyze data from the Beliefs and Attitudes About Memory Survey (BAMS; Brown, Garry, Silver, and Loftus, 1997). We used the original 5-point BAMS data to investigate the functioning of the “Neutral” category via threshold analysis under a 2-class MRM solution. The “Neutral” category was identified as not eliciting the model expected responses and observations in the “Neutral” category were subsequently treated as missing data. For the BAMS data without the “Neutral” category, exploratory MRM analyses specifying up to 5 latent classes were conducted to evaluate data-model fit using the consistent Akaike information criterion (CAIC). For each of three BAMS subscales, a two latent class solution was identified as fitting the mixed Rasch rating scale model the best. Results regarding threshold analysis, person parameters, and item fit based on the final models are presented and discussed as well as the implications of this study.

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An Examination of Personality Characteristics Related to Acquiescence

Christine DiStefano, Grant B. Morgan, and Robert W. Motl

Abstract

Acquiescence, the tendency to agree with statements regardless of content, is often a concern when administering self-report instruments. While there is evidence to support acquiescence as a response style, this reporting tendency may be related to personality factors of individuals. Using a sample of 757 adults, we investigated the Rosenberg Self-Esteem Scale for acquiescence response tendencies by applying the Rasch partial credit model. Results suggested that favorable (i.e., Agree or Strongly Agree) responses were more frequent for the positively worded items than for negatively worded items. Second, the relationship between acquiescence and seven additional personality measures was examined overall and by sex. Among females, acquiescence was correlated with personality measures measuring perceptions by others, whereas acquiescence among males was related to exhibition types of behaviors.

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Construction and Validation of Two Parent-Report Scales for the Evaluation of Early Intervention Programs

William P. Fisher, Jr., Batya Elbaum, and W. Alan Coulter

Abstract

The State Performance Plan (SPP) developed under the 2004 reauthorization of the Individuals with Disabilities Education Act (IDEA 2004, Public Law 108-446) requires states to collect data and report on the impact of early intervention services on three key outcomes for participating families. The NCSEAM Impact on Family Scale (NIFS) and the NCSEAM Family Centered Services Scale (NFCSS) were developed to provide states with a means to address this new reporting requirement and to collect additional data that would inform program improvement efforts. Items suggested by stakeholder groups were piloted with a nationally representative sample of parents of children with developmental delays or disabilities ages birth to three participating in early intervention services in eight states. The 28-item NIFS had measurement reliabilities ranging from .93-.96 in a sample of 1,750; measurement reliabilities for the 135-item NFCSS ranged from .94 to .97 in a sample of 1,755 respondents. A 29-item version of the NFCSS had measurement reliabilities ranging from .87 to .92. Using data from the pilot study, stakeholders established a recommended performance standard, set at a meaningful point in the NIFS item hierarchy, for each of the three established outcome areas.

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Multi-Factor Scale Consolidation When Theory is Weak

Nikolaus Bezruczko and Kyle Perkins

Abstract

As a practical matter, Spirituality and Quality of Life in the health sciences are usually measured separately. Theoretical foundations for this distinction, however, are not strong. In this research, an empirical investigation was conducted into their joint calibration with a Rasch model. Functional Assessment of Cancer Therapy-General (28 items), a cancer health-related quality of life measure (HRQOL), and Functional Assessment of Chronic Illness - Spiritual Well-Being (12 items), a measure of religious and existential well-being (Spirituality), were co-calibrated with a Rasch model implemented with WINSTEPS software for ratings from 545 breast cancer patients. The results show a hierarchical integration of QOL and Spirituality items on a common variable, and both patient separation (2.66) and reliability (.88) improve after co-calibration. Principal Component Analysis of co-calibrated item residuals did not show major threats to dimensionality, and joint calibration explains item variance comparable to separate calibrations (51.9%). Although patient measures (logits) based on separate and co-calibration are within two standard errors, ethnic and racial group values shift after co-calibration.

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Developing an Emotional Distress Item Bank for Cancer Patients

Allen W. Heinemann, Rita K. Bode, Sarah Rosenbloom, and David Cella

Abstract

Emotional distress is common among cancer patients during and after treatment. Many instruments have been used to measure emotional distress; however, none of them has emerged as a standard. Although the diversity of instruments has some merit, the lack of a common measure limits our ability to compare studies. This paper describes how we constructed a 46-item emotional distress bank. Using expert judgment, we selected a pool of items with emotional content from this six-instrument set. Rasch rating scale analysis helped us identify a set of general distress items with good model fit and a measurement gap causing floor effects. Additional items were written to augment the measure where found deficient. The resulting set of items reflects a spectrum of positive and negative affect. The measure demonstrated excellent reliability (person separation reliability = .96) and a wide range of emotional distress and was able to distinguish among levels of disease severity.

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