Corrected Knowledge Alert - PSYCHOMETRIKA

>> Authors:
>> Greve, DN; Brown, GG; Mueller, BA; Glover, G; Liu, TT
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):396-416; JUL 2013
>>
>> Abstract:
>> Functional magnetic resonance imaging (fMRI) is a noninvasive method for
>> measuring brain function by correlating temporal changes in local
>> cerebral blood oxygenation with behavioral measures. fMRI is used to
>> study individuals at single time points, across multiple time points
>> (with or without intervention), as well as to examine the variation of
>> brain function across normal and ill populations. fMRI may be collected
>> at multiple sites and then pooled into a single analysis. This paper
>> describes how fMRI data is analyzed at each of these levels and
>> describes the noise sources introduced at each level.
>>
>> ========================================================================
>>
>>
>> *Pages: 417-440 (Article)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500002
>> *Order Full Text [ ]
>>
>> Title:
>> ASSESSING ITEM FIT FOR UNIDIMENSIONAL ITEM RESPONSE THEORY MODELS USING RESIDUALS FROM ESTIMATED ITEM RESPONSE FUNCTIONS
>>
>> Authors:
>> Haberman, SJ; Sinharay, S; Chon, KH
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):417-440; JUL 2013
>>
>> Abstract:
>> Residual analysis (e.g. Hambleton & Swaminathan, Item response theory:
>> principles and applications, Kluwer Academic, Boston, 1985; Hambleton,
>> Swaminathan, & Rogers, Fundamentals of item response theory, Sage,
>> Newbury Park, 1991) is a popular method to assess fit of item response
>> theory (IRT) models. We suggest a form of residual analysis that may be
>> applied to assess item fit for unidimensional IRT models. The residual
>> analysis consists of a comparison of the maximum-likelihood estimate of
>> the item characteristic curve with an alternative ratio estimate of the
>> item characteristic curve. The large sample distribution of the residual
>> is proved to be standardized normal when the IRT model fits the data. We
>> compare the performance of our suggested residual to the standardized
>> residual of Hambleton et al. (Fundamentals of item response theory,
>> Sage, Newbury Park, 1991) in a detailed simulation study. We then
>> calculate our suggested residuals using data from an operational test.
>> The residuals appear to be useful in assessing the item fit for
>> unidimensional IRT models.
>>
>> ========================================================================
>>
>>
>> *Pages: 441-463 (Article)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500003
>> *Order Full Text [ ]
>>
>> Title:
>> ON THE LIKELIHOOD RATIO TESTS IN BIVARIATE ACDE MODELS
>>
>> Authors:
>> Wu, H; Neale, MC
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):441-463; JUL 2013
>>
>> Abstract:
>> The ACE and ADE models have been heavily exploited in twin studies to
>> identify the genetic and environmental components in phenotypes.
>> However, the validity of the likelihood ratio test (LRT) of the
>> existence of a variance component, a key step in the use of such models,
>> has been doubted because the true values of the parameters lie on the
>> boundary of the parameter space of the alternative model for such tests,
>> violating a regularity condition required for a LRT (e.g., Carey in
>> Behav. Genet. 35:653-665, 2005; Visscher in Twin Res. Hum. Genet.
>> 9:490-495, 2006). Dominicus, Skrondal, Gjessing, Pedersen, and Palmgren
>> (Behav. Genet. 36:331-340, 2006) solve the problem of testing univariate
>> components in ACDE models. Our current work as presented in this paper
>> resolves the issue of LRTs in bivariate ACDE models by exploiting the
>> theoretical frameworks of inequality constrained LRTs based on cone
>> approximations. Our derivation shows that the asymptotic sampling
>> distribution of the test statistic for testing a single bivariate
>> component in an ACE or ADE model is a mixture of chi(2) distributions of
>> degrees of freedom (dfs) ranging from 0 to 3, and that for testing both
>> the A and C (or D) components is one of dfs ranging from 0 to 6. These
>> correct distributions are stochastically smaller than the chi(2)
>> distributions in traditional LRTs and therefore LRTs based on these
>> distributions are more powerful than those used naively. Formulas for
>> calculating the weights are derived and the sampling distributions are
>> confirmed by simulation studies. Several invariance properties for
>> normal data (at most) missing by person are also proved. Potential
>> generalizations of this work are also discussed.
>>
>> ========================================================================
>>
>>
>> *Pages: 464-480 (Article)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500004
>> *Order Full Text [ ]
>>
>> Title:
>> IRT TEST EQUATING IN COMPLEX LINKAGE PLANS
>>
>> Authors:
>> Battauz, M
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):464-480; JUL 2013
>>
>> Abstract:
>> Linkage plans can be rather complex, including many forms, several
>> links, and the connection of forms through different paths. This article
>> studies item response theory equating methods for complex linkage plans
>> when the common-item nonequivalent group design is used. An efficient
>> way to average equating coefficients that link the same two forms
>> through different paths will be presented and the asymptotic standard
>> errors of indirect and average equating coefficients are derived. The
>> methodology is illustrated using simulations studies and a real data
>> example.
>>
>> ========================================================================
>>
>>
>> *Pages: 481-497 (Article)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500005
>> *Order Full Text [ ]
>>
>> Title:
>> USING DETERMINISTIC, GATED ITEM RESPONSE THEORY MODEL TO DETECT TEST CHEATING DUE TO ITEM COMPROMISE
>>
>> Authors:
>> Shu, Z; Henson, R; Luecht, R
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):481-497; JUL 2013
>>
>> Abstract:
>> The Deterministic, Gated Item Response Theory Model (DGM, Shu,
>> Unpublished Dissertation. The University of North Carolina at
>> Greensboro, 2010) is proposed to identify cheaters who obtain
>> significant score gain on tests due to item exposure/compromise by
>> conditioning on the item status (exposed or unexposed items). A "gated"
>> function is introduced to decompose the observed examinees' performance
>> into two distributions (the true ability distribution determined by
>> examinees' true ability and the cheating distribution determined by
>> examinees' cheating ability). Test cheaters who have score gain due to
>> item exposure are identified through the comparison of the two
>> distributions. Hierarchical Markov Chain Monte Carlo is used as the
>> model's estimation framework. Finally, the model is applied in a real
>> data set to illustrate how the model can be used to identify examinees
>> having pre-knowledge on the exposed items.
>>
>> ========================================================================
>>
>>
>> *Pages: 498-525 (Article)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500006
>> *Order Full Text [ ]
>>
>> Title:
>> MULTIOBJECTIVE BLOCKMODELING FOR SOCIAL NETWORK ANALYSIS
>>
>> Authors:
>> Brusco, M; Doreian, P; Steinley, D; Satornino, CB
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):498-525; JUL 2013
>>
>> Abstract:
>> To date, most methods for direct blockmodeling of social network data
>> have focused on the optimization of a single objective function.
>> However, there are a variety of social network applications where it is
>> advantageous to consider two or more objectives simultaneously. These
>> applications can broadly be placed into two categories: (1) simultaneous
>> optimization of multiple criteria for fitting a blockmodel based on a
>> single network matrix and (2) simultaneous optimization of multiple
>> criteria for fitting a blockmodel based on two or more network matrices,
>> where the matrices being fit can take the form of multiple indicators
>> for an underlying relationship, or multiple matrices for a set of
>> objects measured at two or more different points in time. A
>> multiobjective tabu search procedure is proposed for estimating the set
>> of Pareto efficient blockmodels. This procedure is used in three
>> examples that demonstrate possible applications of the multiobjective
>> blockmodeling paradigm.
>>
>> ========================================================================
>>
>>
>> *Pages: 526-537 (Article)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500007
>> *Order Full Text [ ]
>>
>> Title:
>> OBLIQUE ROTATON IN CANONICAL CORRELATION ANALYSIS REFORMULATED AS MAXIMIZING THE GENERALIZED COEFFICIENT OF DETERMINATION
>>
>> Authors:
>> Satomura, H; Adachi, K
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):526-537; JUL 2013
>>
>> Abstract:
>> To facilitate the interpretation of canonical correlation analysis (CCA)
>> solutions, procedures have been proposed in which CCA solutions are
>> orthogonally rotated to a simple structure. In this paper, we consider
>> oblique rotation for CCA to provide solutions that are much easier to
>> interpret, though only orthogonal rotation is allowed in the existing
>> formulations of CCA. Our task is thus to reformulate CCA so that its
>> solutions have the freedom of oblique rotation. Such a task can be
>> achieved using Yanai's (Jpn. J. Behaviormetrics 1:46-54, 1974; J. Jpn.
>> Stat. Soc. 11:43-53, 1981) generalized coefficient of determination for
>> the objective function to be maximized in CCA. The resulting solutions
>> are proved to include the existing orthogonal ones as special cases and
>> to be rotated obliquely without affecting the objective function value,
>> where ten Berge's (Psychometrika 48:519-523, 1983) theorems on
>> suborthonormal matrices are used. A real data example demonstrates that
>> the proposed oblique rotation can provide simple, easily interpreted CCA
>> solutions.
>>
>> ========================================================================
>>
>>
>> *Pages: 538-544 (Article)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500008
>> *Order Full Text [ ]
>>
>> Title:
>> A NOTE ON THE HIERARCHICAL MODEL FOR RESPONSES AND RESPONSE TIMES IN TESTS OF VAN DER LINDEN (2007)
>>
>> Authors:
>> Ranger, J
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):538-544; JUL 2013
>>
>> Abstract:
>> Findings suggest that in psychological tests not only the responses but
>> also the times needed to give the responses are related to
>> characteristics of the test taker. This observation has stimulated the
>> development of latent trait models for the joint distribution of the
>> responses and the response times. Such models are motivated by the hope
>> to improve the estimation of the latent traits by additionally
>> considering response time. In this article, the potential relevance of
>> the response times for psychological assessment is explored for the
>> model of van der Linden (Psychometrika 72:287-308, 2007) that seems to
>> have become the standard approach to response time modeling in
>> educational testing. It can be shown that the consideration of response
>> times increases the information of the test. However, one also can prove
>> that the contribution of the response times to the test information is
>> bounded and has a simple limit.
>>
>> ========================================================================
>>
>>
>> *Pages: 545-552 (Article)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500009
>> *Order Full Text [ ]
>>
>> Title:
>> CONTINUOUS ORTHOGONAL COMPLEMENT FUNCTIONS AND DISTRIBUTION-FREE GOODNESS OF FIT TESTS IN MOMENT STRUCTURE
>>
>> Authors:
>> Jennrich, R; Satorra, A
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):545-552; JUL 2013
>>
>> Abstract:
>> It is shown that for any full column rank matrix X-0 with more rows than
>> columns there is a neighborhood N of X-0 and a continuous function f on
>> N such that f (X) is an orthogonal complement of X for all X in N. This
>> is used to derive a distribution free goodness of fit test for
>> covariance structure analysis. This test was proposed some time ago and
>> is extensively used. Unfortunately, there is an error in the proof that
>> the proposed test statistic has an asymptotic chi(2) distribution. This
>> is a potentially serious problem, without a proof the test statistic may
>> not, in fact, be asymptoticly chi(2). The proof, however, is easily
>> fixed using a continuous orthogonal complement function. Similar
>> problems arise in other applications where orthogonal complements are
>> used. These can also be resolved by using continuous orthogonal
>> complement functions.
>>
>> ========================================================================
>>
>>
>> *Pages: 554-555 (Correction)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500010
>> *Order Full Text [ ]
>>
>> Title:
>> USING THE CRITERION-PREDICTOR FACTOR MODEL TO COMPUTE THE PROBABILITY OF DETECTING PREDICTION BIAS WITH ORDINARY LEAST SQUARES REGRESSION (vol 77, pg 561, 2012)
>>
>> Authors:
>> Culpepper, SA
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):554-555; JUL 2013
>>
>> ========================================================================
>>
>>
>> *Pages: 556-556 (Correction)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500011
>> *Order Full Text [ ]
>>
>> Title:
>> EXPLORATORY BI-FACTOR ANALYSIS (vol 76, pg 537, 2011)
>>
>> Authors:
>> Jennrich, RI; Bentler, PM
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):556-556; JUL 2013
>>
>> ========================================================================
>>
>>
>> *Pages: 557-575 (Article)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500012
>> *Order Full Text [ ]
>>
>> Title:
>> MONITORING SCALE SCORES OVER TIME VIA QUALITY CONTROL CHARTS, MODEL-BASED APPROACHES, AND TIME SERIES TECHNIQUES
>>
>> Authors:
>> Lee, YH; von Davier, AA
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):557-575; JUL 2013
>>
>> Abstract:
>> Maintaining a stable score scale over time is critical for all
>> standardized educational assessments. Traditional quality control tools
>> and approaches for assessing scale drift either require special equating
>> designs, or may be too time-consuming to be considered on a regular
>> basis with an operational test that has a short time window between an
>> administration and its score reporting. Thus, the traditional methods
>> are not sufficient to catch unusual testing outcomes in a timely manner.
>> This paper presents a new approach for score monitoring and assessment
>> of scale drift. It involves quality control charts, model-based
>> approaches, and time series techniques to accommodate the following
>> needs of monitoring scale scores: continuous monitoring, adjustment of
>> customary variations, identification of abrupt shifts, and assessment of
>> autocorrelation. Performance of the methodologies is evaluated using
>> manipulated data based on real responses from 71 administrations of a
>> large-scale high-stakes language assessment.
>>
>> ========================================================================
>>
>>
>> *Pages: 576-600 (Article)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500013
>> *Order Full Text [ ]
>>
>> Title:
>> DETECTING INTERVENTION EFFECTS USING A MULTILEVEL LATENT TRANSITION ANALYSIS WITH A MIXTURE IRT MODEL
>>
>> Authors:
>> Cho, SJ; Cohen, AS; Bottge, B
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):576-600; JUL 2013
>>
>> Abstract:
>> A multilevel latent transition analysis (LTA) with a mixture IRT
>> measurement model (MixIRTM) is described for investigating the
>> effectiveness of an intervention. The addition of a MixIRTM to the
>> multilevel LTA permits consideration of both potential heterogeneity in
>> students' response to instructional intervention as well as a
>> methodology for assessing stage sequential change over time at both
>> student and teacher levels. Results from an LTA-MixIRTM and multilevel
>> LTA-MixIRTM were compared in the context of an educational intervention
>> study. Both models were able to describe homogeneities in problem
>> solving and transition patterns. However, ignoring a multilevel
>> structure in LTA-MixIRTM led to different results in group membership
>> assignment in empirical results. Results for the multilevel LTA-MixIRTM
>> indicated that there were distinct individual differences in the
>> different transition patterns. The students receiving the intervention
>> treatment outscored their business as usual (i.e., control group)
>> counterparts on the curriculum-based Fractions Computation test. In
>> addition, 27.4 % of the students in the sample moved from the low
>> ability student-level latent class to the high ability student-level
>> latent class. Students were characterized differently depending on the
>> teacher-level latent class.
>>
>> ========================================================================
>>
>>
>> *Pages: 601-603 (Book Review)
>> *View Full Record: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=CCC&DestLinkType=FullRecord;KeyUT=CCC:000320446500014
>> *Order Full Text [ ]
>>
>> Title:
>> Elements of Adaptive Testing
>>
>> Authors:
>> Ali, US; van Rijn, PW
>>
>> Source:
>> *PSYCHOMETRIKA*, 78 (3):601-603; JUL 2013
>>
>>