Tracing children's vocabulary development from preschool through the school‐age years: an 8‐year longitudinal study

In this 8‐year longitudinal study, we traced the vocabulary growth of Chinese children, explored potential precursors of vocabulary knowledge, and investigated how vocabulary growth predicted future reading skills. Two hundred and sixty‐four (264) native Chinese children from Beijing were measured on a variety of reading and language tasks over 8 years. Between the ages of 4 to 10 years, they were administered tasks of vocabulary and related cognitive skills. At age 11, comprehensive reading skills, including character recognition, reading fluency, and reading comprehension were examined. Individual differences in vocabulary developmental profiles were estimated using the intercept‐slope cluster method. Vocabulary development was then examined in relation to later reading outcomes. Three subgroups of lexical growth were classified, namely high‐high (with a large initial vocabulary size and a fast growth rate), low‐high (with a small initial vocabulary size and a fast growth rate) and low‐low (with a small initial vocabulary size and a slow growth rate) groups. Low‐high and low‐low groups were distinguishable mostly through phonological skills, morphological skills and other reading‐related cognitive skills. Childhood vocabulary development (using intercept and slope) explained subsequent reading skills. Findings suggest that language‐related and reading‐related cognitive skills differ among groups with different developmental trajectories of vocabulary, and the initial size and growth rate of vocabulary may be two predictors for later reading development.     

The satisfaction and stress of being a market maven: A social network perspective

Compared with the average consumer, market mavens possess a unique set of characteristics including a greater depth of knowledge of the marketplace and its products, as well as a strong social network. Based on a field study of an emerging social network of Canadian undergraduate students (N = 71), we examine the level of satisfaction and stress that market mavens experience as a result of their network participation. First, market mavens (versus non‐mavens) are more satisfied with their network if they occupy central network positions. Simultaneously, however, mavens incur more stress if they occupy these central positions. Further, market mavens have a lower rate of network growth and build a more a selective network of like‐minded others over time. This suggests that market mavens seek to interact with other market mavens more so than with non‐mavens about product‐related and market‐related information. Together, we provide new insights into the personal outcomes of market mavens' network positions and their networking behavior. Copyright © 2015 John Wiley & Sons, Ltd.     

Fitting direct covariance structures by the MSTRUCT modeling language of the CALIS procedure

This paper demonstrates the usefulness and flexibility of the general structural equation modelling (SEM) approach to fitting direct covariance patterns or structures (as opposed to fitting implied covariance structures from functional relationships among variables). In particular, the MSTRUCT modelling language (or syntax) of the CALIS procedure (SAS/STAT version 9.22 or later: SAS Institute, 2010) is used to illustrate the SEM approach. The MSTRUCT modelling language supports a direct covariance pattern specification of each covariance element. It also supports the input of additional independent and dependent parameters. Model tests, fit statistics, estimates, and their standard errors are then produced under the general SEM framework. By using numerical and computational examples, the following tests of basic covariance patterns are illustrated: sphericity, compound symmetry, and multiple‐group covariance patterns. Specification and testing of two complex correlation structures, the circumplex pattern and the composite direct product models with or without composite errors and scales, are also illustrated by the MSTRUCT syntax. It is concluded that the SEM approach offers a general and flexible modelling of direct covariance and correlation patterns. In conjunction with the use of SAS macros, the MSTRUCT syntax provides an easy‐to‐use interface for specifying and fitting complex covariance and correlation structures, even when the number of variables or parameters becomes large.     

Polytomous multilevel testlet models for testlet‐based assessments with complex sampling designs

A pplications of standard item response theory models assume local independence of items and persons. This paper presents polytomous multilevel testlet models for dual dependence due to item and person clustering in testlet‐based assessments with clustered samples. Simulation and survey data were analysed with a multilevel partial credit testlet model. This model was compared with three alternative models – a testlet partial credit model (PCM), multilevel PCM, and PCM – in terms of model parameter estimation. The results indicated that the deviance information criterion was the fit index that always correctly identified the true multilevel testlet model based on the quantified evidence in model selection, while the Akaike and Bayesian information criteria could not identify the true model. In general, the estimation model and the magnitude of item and person clustering impacted the estimation accuracy of ability parameters, while only the estimation model and the magnitude of item clustering affected the item parameter estimation accuracy. Furthermore, ignoring item clustering effects produced higher total errors in item parameter estimates but did not have much impact on the accuracy of ability parameter estimates, while ignoring person clustering effects yielded higher total errors in ability parameter estimates but did not have much effect on the accuracy of item parameter estimates. When both clustering effects were ignored in the PCM, item and ability parameter estimation accuracy was reduced.     

Role of centrifugal projections to the olfactory bulb in olfactory processing

While there is evidence that feedback projections from cortical and neuromodulatory structures to the olfactory bulb are crucial for maintaining the oscillatory dynamics of olfactory bulb processing, it is not clear how changes in dynamics are related to odor perception. Using electrical lesions of the olfactory peduncle, sparing output from the olfactory bulb while decreasing feedback inputs to the olfactory bulb, we demonstrate here a role for feedback inputs to the olfactory bulb in the formation of odor-reward associations, but not for maintaining primary bulbar odor representations, as reflected by spontaneous odor discrimination.     

Implications of direct and indirect range restriction for meta-analysis methods and findings

Range restriction in most data sets is indirect, but the meta-analysis methods used to date have applied the correction for direct range restriction to data in which range restriction is indirect. The authors show that this results in substantial undercorrections for the effects of range restriction, and they present meta-analysis methods for making accurate corrections when range restriction is indirect. Applying these methods to a well-known large-sample empirical database, the authors estimate that previous meta-analyses have underestimated the correlation between general mental ability and job performance by about 25%, indicating that this is potentially an important methodological issue in meta-analysis in general.     

Statistical manifold as an affine space: A functional equation approach

A statistical manifold M_μ consists of positive functions f such that defines a probability measure. In order to define an atlas on the manifold, it is viewed as an affine space associated with a subspace of the Orlicz space L^Φ. This leads to a functional equation whose solution, after imposing the linearity constrain in line with the vector space assumption, gives rise to a general form of mappings between the affine probability manifold and the vector (Orlicz) space. These results generalize the exponential statistical manifold and clarify some foundational issues in non-parametric information geometry.     

Deconstructing therapy outcome measurement with Rasch analysis of a measure of general clinical distress: the Symptom Checklist-90-Revised

Rasch analysis was used to illustrate the usefulness of item-level analyses for evaluating a common therapy outcome measure of general clinical distress, the Symptom Checklist-90-Revised (SCL-90-R; Derogatis, 1994). Using complementary therapy research samples, the instrument's 5-point rating scale was found to exceed clients' ability to make reliable discriminations and could be improved by collapsing it into a 3-point version (combining scale points 1 with 2 and 3 with 4). This revision, in addition to removing 3 misfitting items, increased person separation from 4.90 to 5.07 and item separation from 7.76 to 8.52 (resulting in alphas of .96 and .99, respectively). Some SCL-90-R subscales had low internal consistency reliabilities; SCL-90-R items can be used to define one factor of general clinical distress that is generally stable across both samples, with two small residual factors.