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1.
The population discrepancy between unstandardized and standardized reliability of homogeneous multicomponent measuring instruments is examined. Within a latent variable modeling framework, it is shown that the standardized reliability coefficient for unidimensional scales can be markedly higher than the corresponding unstandardized reliability coefficient, or alternatively substantially lower than the latter. Based on these findings, it is recommended that scholars avoid estimating, reporting, interpreting, or using standardized scale reliability coefficients in empirical research, unless they have strong reasons to consider standardizing the original components of utilized scales.  相似文献   

2.
The purpose of this study is to provide guidance on a process for including latent class predictors in regression mixture models. We first examine the performance of current practice for using the 1-step and 3-step approaches where the direct covariate effect on the outcome is omitted. None of the approaches show adequate estimates of model parameters. Given that Step 1 of the 3-step approach shows adequate results in class enumeration, we suggest using an alternative approach: (a) decide the number of latent classes without predictors of latent classes, and (b) bring the latent class predictors into the model with the inclusion of hypothesized direct covariate effects. Our simulations show that this approach leads to good estimates for all model parameters. The proposed approach is demonstrated by using empirical data to examine the differential effects of family resources on students’ academic achievement outcome. Implications of the study are discussed.  相似文献   

3.
This article studies the difference between the criterion validity coefficient of the widely used overall scale score for a unidimensional multicomponent measuring instrument and the maximal criterion validity coefficient that is achievable with a linear combination of its components. A necessary and sufficient condition of their identity is presented in the case of measurement errors being uncorrelated among themselves and with a used criterion. An upper bound of the difference in these validity coefficients is provided, indicating that it cannot exceed the discrepancy between the maximal reliability and composite reliability indexes. A readily applicable latent variable modeling procedure is discussed that can be used for point and interval estimation of the difference between the maximal and scale criterion validity coefficients. The outlined method is illustrated with a numerical example.  相似文献   

4.
Researchers use latent class growth (LCG) analysis to detect meaningful subpopulations that display different growth curves. However, especially when the number of classes required to obtain a good fit is large, interpretation of the encountered class-specific curves might not be straightforward. To overcome this problem, we propose an alternative way of performing LCG analysis, which we call LCG tree (LCGT) modeling. For this purpose, a recursive partitioning procedure similar to divisive hierarchical cluster analysis is used: Classes are split until a certain criterion indicates that the fit does not improve. The advantage of the LCGT approach compared to the standard LCG approach is that it gives a clear insight into how the latent classes are formed and how solutions with different numbers of classes relate. The practical use of the approach is illustrated using applications on drug use during adolescence and mood regulation during the day.  相似文献   

5.
This study addresses the question of why spellings determined by morphology are relatively hard to acquire by presenting a latent class model of children's acquisition of a doublet of consonants in the spelling of Dutch verbs. This spelling pattern can be determined either by a phonological rule (after a short vowel, a doublet is spelled) or a morphological rule (doublets are spelled in past-tense forms). The results show that the youngest group of spellers identified by latent class analysis predominantly used an alphabetic strategy. They did not spell doublets at all. The latent class model further shows that the acquisition of phonologically determined spellings occurred at a lower average age than the acquisition of morphologically determined spellings. The latter led to overgeneralizations, and a U-shaped developmental pattern was found as a consequence of these overgeneralizations. Children over generalized doublets for different reasons. At younger ages, overgeneralizations of doublets occurred because children treated the doublet as a phonological alternative to the singleton, whereas at older ages, overgeneralizations of doublets were confined to homophones, indicating lexical effects.  相似文献   

6.
The primary purpose of this study is to investigate the mathematical characteristics of the test reliability coefficient ρ XX′ as a function of item response theory (IRT) parameters and present the lower and upper bounds of the coefficient. Another purpose is to examine relative performances of the IRT reliability statistics and two classical test theory (CTT) reliability statistics (Cronbach’s alpha and Feldt–Gilmer congeneric coefficients) under various testing conditions that result from manipulating large-scale real data. For the first purpose, two alternative ways of exactly quantifying ρ XX′ are compared in terms of computational efficiency and statistical usefulness. In addition, the lower and upper bounds for ρ XX′ are presented in line with the assumptions of essential tau-equivalence and congeneric similarity, respectively. Empirical studies conducted for the second purpose showed across all testing conditions that (1) the IRT reliability coefficient was higher than the CTT reliability statistics; (2) the IRT reliability coefficient was closer to the Feldt–Gilmer coefficient than to the Cronbach’s alpha coefficient; and (3) the alpha coefficient was close to the lower bound of IRT reliability. Some advantages of the IRT approach to estimating test-score reliability over the CTT approaches are discussed in the end.  相似文献   

7.
Latent Markov models with covariates can be estimated via 1-step maximum likelihood. However, this 1-step approach has various disadvantages, such as that the inclusion of covariates in the model might alter the formation of the latent states and that parameter estimation could become infeasible with large numbers of time points, responses, and covariates. This is why researchers typically prefer performing the analysis in a stepwise manner; that is, they first construct the measurement model, then obtain the latent state classifications, and subsequently study the relationship between covariates and latent state memberships. However, such a stepwise approach yields downward-biased estimates of the covariate effects on initial state and transition probabilities. This article, shows how to overcome this problem using a generalization of the bias-corrected 3-step estimation method proposed for latent class analysis (Asparouhov & Muthén, 2014; Bolck, Croon, & Hagenaars, 2004; Vermunt, 2010). We give a formal derivation of the generalization to latent Markov models and discuss how it can be used with many time points by incorporating it into a Baum–Welch type of expectation-maximization algorithm. We evaluate the method through a simulation study and illustrate it using an application on household financial portfolio change. Our study shows that the proposed correction method yields unbiased parameter estimates and accurate standard errors, except for situations with very poorly separated classes and a small sample.  相似文献   

8.
Popular longitudinal models allow for prediction of growth trajectories in alternative ways. In latent class growth models (LCGMs), person-level covariates predict membership in discrete latent classes that each holistically define an entire trajectory of change (e.g., a high-stable class vs. late-onset class vs. moderate-desisting class). In random coefficient growth models (RCGMs, also known as latent curve models), however, person-level covariates separately predict continuously distributed latent growth factors (e.g., an intercept vs. slope factor). This article first explains how complex and nonlinear interactions between predictors and time are recovered in different ways via LCGM versus RCGM specifications. Then a simulation comparison illustrates that, aside from some modest efficiency differences, such predictor relationships can be recovered approximately equally well by either model—regardless of which model generated the data. Our results also provide an empirical rationale for integrating findings about prediction of individual change across LCGMs and RCGMs in practice.  相似文献   

9.
A latent variable modeling method for studying maximal reliability of unidimensional multicomponent measuring instruments with correlated errors is outlined. In the presence of correlation between 2 residual terms, the procedure allows one to point and interval estimate the reliability of the linear combination of the scale components that possesses the highest possible reliability coefficient. The approach is readily applicable with popular latent variable modeling software and also provides an alternative scoring rule to the widely used overall sum score for homogeneous psychometric scales. The discussed method is illustrated with a numerical example.  相似文献   

10.
This article is a pedagogical piece on coefficient alpha (α) and its uses. The classical approach to test reliability is explained. Test‐retest, alternative‐forms, and internal‐consistency methods of approximating test reliability are described, equations are derived for each method, and α is shown to be a lower‐bound internal‐consistency approximation to test reliability. Emphasis is placed on the effects of violations of model assumptions on reliability estimation. The classical models are conceptualized as structural equation models and are displayed in path diagrams. Special emphasis is placed on the failure of α to meet certain basic criteria as an index of test homogeneity.  相似文献   

11.
A model is proposed for identifying latent predictor score patterns associated with a latent outcome variable. The model employs 2 new devices: (a) a path coefficient vector of contrast coefficients to describe a configural pattern in a structural model, and (b) a new type of latent variable with values that quantify the match of the person's latent predictor variable profile pattern to a theoretical pattern associated with the factor. The model is illustrated using data on perceptions and evaluations of political candidates during a debate. Findings suggest a pattern of scores on the perceptual variables associated with perceived debate success for female observers but not for male observers.  相似文献   

12.
Multiple-choice reading comprehension items from a conventional, norm-referenced reading comprehension test are successfully analyzed using a simple latent class model. A classification rule for assigning respondents to "mastery" or "nonmastery" states is presented which simplifies the scoring procedure of Macready and Dayton (1977). A procedure is also derived for estimating the "true," or "disattenuated," latent cross-classification of masters versus nonmasters for two tests, and illustrated using two sets of items from the same content domain. Results support the use of latent class, state mastery models with more heterogeneous item pools than has been advocated by previous authors.  相似文献   

13.
I discuss the contribution by Davenport, Davison, Liou, & Love (2015) in which they relate reliability represented by coefficient α to formal definitions of internal consistency and unidimensionality, both proposed by Cronbach (1951). I argue that coefficient α is a lower bound to reliability and that concepts of internal consistency and unidimensionality, however defined, belong to the realm of validity, viz. the issue of what the test measures. Internal consistency and unidimensionality may play a role in the construction of tests when the theory of the attribute for which the test is constructed implies that the items be internally consistent or unidimensional. I also offer examples of attributes that do not imply internal consistency or unidimensionality, thus limiting these concepts' usefulness in practical applications.  相似文献   

14.
This article examines the effects of clustering in latent class analysis. A comprehensive simulation study is conducted, which begins by specifying a true multilevel latent class model with varying within- and between-cluster sample sizes, varying latent class proportions, and varying intraclass correlations. These models are then estimated under the assumption of a single-level latent class model. The outcomes of interest are measures of bias in the Bayesian Information Criterion (BIC) and the entropy R 2 statistic relative to accounting for the multilevel structure of the data. The results indicate that the size of the intraclass correlation as well as between- and within-cluster sizes are the most prominent factors in determining the amount of bias in these outcome measures, with increasing intraclass correlations combined with small between-cluster sizes resulting in increased bias. Bias is particularly noticeable in the BIC. In addition, there is evidence that class separation interacts with the size of the intraclass correlations and cluster sizes in producing bias in these measures.  相似文献   

15.
This study investigates the effect of multidimensionality on extraction of latent classes in mixture Rasch models. In this study, two‐dimensional data were generated under varying conditions. The two‐dimensional data sets were analyzed with one‐ to five‐class mixture Rasch models. Results of the simulation study indicate the mixture Rasch model tended to extract more latent classes than the number of dimensions simulated, particularly when the multidimensional structure of the data was more complex. In addition, the number of extracted latent classes decreased as the dimensions were more highly correlated regardless of multidimensional structure. An analysis of the empirical multidimensional data also shows that the number of latent classes extracted by the mixture Rasch model is larger than the number of dimensions measured by the test.  相似文献   

16.
The precision of estimates in many statistical models can be expressed by a confidence interval (CI). CIs based on standard errors (SEs) are common in practice, but likelihood-based CIs are worth consideration. In comparison to SEs, likelihood-based CIs are typically more difficult to estimate, but are more robust to model (re)parameterization. In latent variable models, some parameters might take on values outside of their interpretable range. Therefore, it is desirable to place a bound to keep the parameter interpretable. For likelihood-based CI, a correction is needed when a parameter is bounded. The correction is known (Wu & Neale, 2012), but is difficult to implement in practice. A novel automatic implementation that is simple for an applied researcher to use is introduced. A simulation study demonstrates the accuracy of the correction using a latent growth curve model and the method is illustrated with a multilevel confirmatory factor analysis.  相似文献   

17.
Sometimes, test‐takers may not be able to attempt all items to the best of their ability (with full effort) due to personal factors (e.g., low motivation) or testing conditions (e.g., time limit), resulting in poor performances on certain items, especially those located toward the end of a test. Standard item response theory (IRT) models fail to consider such testing behaviors. In this study, a new class of mixture IRT models was developed to account for such testing behavior in dichotomous and polytomous items, by assuming test‐takers were composed of multiple latent classes and by adding a decrement parameter to each latent class to describe performance decline. Parameter recovery, effect of model misspecification, and robustness of the linearity assumption in performance decline were evaluated using simulations. It was found that the parameters in the new models were recovered fairly well by using the freeware WinBUGS; the failure to account for such behavior by fitting standard IRT models resulted in overestimation of difficulty parameters on items located toward the end of the test and overestimation of test reliability; and the linearity assumption in performance decline was rather robust. An empirical example is provided to illustrate the applications and the implications of the new class of models.  相似文献   

18.
This article shows how to extend the inferential test of Shipley (2000b), which is applicable to recursive path models without correlated errors (a directed acyclic graph [DAG] model), to a class of recursive path models that include correlated errors (a semi-Markov model). The path model is first converted to a partial ancestral graph (PAG) and then, for PAGs that do not require latent variables, an inducing path DAG is obtained that is equivalent in its conditional independence relations to the original path model. The null probabilities of the k tests of independence that are implied by this DAG are combined using Fisher's test statistic C = -2ΣLn(pi), which is distributed as a chi-square variate with 2k degrees of freedom.  相似文献   

19.
This study focused on misspecifications in composing parcels to represent a latent construct. Two measurement design factors, item reliability and intercorrelations among parcels, defined 12 true unidimensional parcel models. Deviations from the true model were examined via a 2-facet measurement model in which items and parcels represented the 2 facets. Unidimensionality was examined using a set of criteria developed for the 2-facet measurement model. Many misspecified parcel models produced admissible factor loadings despite poor overall fit and unacceptable residual covariances. The factor loadings alone may not be sufficient for evaluating latent factor representation. The findings suggest that parcels' unidimensionality should be analyzed before the measurement model to which they belong is entered into a comprehensive structural model. The 2-facet measurement model provides a relevant assessment of unidimensionality of the parcel compositions.  相似文献   

20.
This study investigated using latent class analysis to set performance standards for assessments comprised of multiple-choice and performance assessment items. Employing this procedure, it is possible to use a sample of student responses to accomplish four goals: (a) determine how well a specified latent structure fits student performance data; (b) determine which latent structure best represents the relationships in the data; (c) obtain estimates of item parameters for each latent class; and (d) identify to which class within that latent structure each response pattern most likely belongs. Comparisons with the Angoff and profile rating methods revealed that the approaches agreed with each other quite well, indicating that both empirical and test-based judgmental approaches may be used for setting performance standards for student achievement.  相似文献   

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