bluuebunny/crossref_metadata_2025_split huggingface dataset:
Paroxysmal Events in Infants: Persistent Eye Closure Makes Seizures Unlikely
Authors: Korff Christian M. , Nordli Douglas R. 
Published: September 2005

Objective. Paroxysmal events are frequent in infancy. A precise diagnosis is often difficult to assign despite adequate history and physical examination. Certain clinical signs may help to suggest the diagnosis, thereby avoiding unnecessary and costly investigations. The aim of this study was to determine the frequency of eye opening during infantile seizures and evaluate the potential usefulness of this simple observation in the differential diagnosis of acute events in infants.
Methods. We performed a retrospective video electroencephalogram review of the seizures recorded in infants at our Epilepsy Center, paying specific attention to eye opening.
Results. Ninety-one seizures in 69 infants were included. Eyes were open in 85 (93.4%) cases.
Conclusions. Infants whose eyes are closed throughout the paroxysmal event are most likely not having seizures.
Lead Exposure in Children: Prevention, Detection, and Management
Authors:   Committee on Environmental Health
Published: September 2005

This Policy Statement was retired April 2013.
Fatal lead encephalopathy has disappeared and blood lead concentrations have decreased in US children, but approximately 25% still live in housing with deteriorated lead-based paint and are at risk of lead exposure with resulting cognitive impairment and other sequelae. Evidence continues to accrue that commonly encountered blood lead concentrations, even those less than 10 μg/dL, may impair cognition, and there is no threshold yet identified for this effect. Most US children are at sufficient risk that they should have their blood lead concentration measured at least once. There is now evidence-based guidance available for managing children with increased lead exposure. Housing stabilization and repair can interrupt exposure in most cases. The focus in childhood lead-poisoning policy, however, should shift from case identification and management to primary prevention, with a goal of safe housing for all children.
Trends in Contacts With Mental Health Professionals and Cost Barriers to Mental Health Care Among Adults With Significant Psychological Distress in the United States: 1997–2002
Authors: Mojtabai Ramin 
Published: September 2005

Objectives. I assessed recent trends in prevalence of any contact with mental health professionals and nonuse of mental health care or prescription medications owing to cost among adults with significant psychological distress. Methods. In samples drawn from the National Health Interview Survey of 1997–2002, multiple logistic regression analysis was used to examine the association of survey year with mental health professional contacts and nonuse of mental health care or prescription medications owing to cost. Results. The prevalence of any contact with mental health professionals increased from 29.1% in 1997 to 35.5% in 2002 (P<.05). The prevalence of nonuse of services because of cost also increased—from 15.6% to 20.0% for mental health care (P<.05) and from 27.7% to 34.1% for medication use (P<.001). Age, racial/ethnic, income, and insurance status disparities in receiving care persisted over the study period. Conclusions. The number of individuals in need of mental health care who contacted mental health professionals grew in recent years, as did the number of individuals who encountered cost barriers to such care. Barring dramatic improvements in health insurance coverage, more individuals will likely face such barriers in coming years.
Running on Empty: Families, Time, and Workplace Injuries
Authors: Boden Leslie I. 
Published: September 2005

Over the past 5 decades, more women have entered the labor force, and more households have been headed by single parents. Both trends have substantially reduced parents’ free time, creating added strain in the event of family health problems, including work-related injuries and illnesses. This commentary presents evidence about the impact of occupational injuries on today’s families. In addition to losing considerable income, injured parents are less able to do household work, and other family members are often called on to care for them. Family members cut back on their paid, school, and household work to fill in for the injured parent. This suggests the importance of policies to help today’s time-strapped families cope with major family health events.
Young Adult Caregivers: A First Look at an Unstudied Population
Authors: Levine Carol , Hunt Gail Gibson , Halper Deborah , Hart Andrea Y. , Lautz Jessica , Gould David A. 
Published: September 2005

Objectives. We examined the prevalence, characteristics, and responsibilities of young adults aged 18 to 25 years who are caregivers for ill, elderly, or disabled family members or friends. Methods. We analyzed 2 previously published national studies (from 1998 and 2004) of adult caregivers. Results. Young adult caregivers make up between 12% and 18% of the total number of adult caregivers. Over half are male, and the average age is 21. Most young adults are caring for a female relative, most often a grandmother. Young adult caregivers identified a variety of unmet needs, including obtaining medical help, information, and help making end-of-life decisions. Conclusions. Analysis of these 2 surveys broadens our understanding of the spectrum of family caregivers by focusing on caregivers between the ages of 18 and 25 years. The high proportion of young men raises questions about the appropriateness of current support services, which are typically used by older women. Concerted efforts are essential to ensure that young adults who become caregivers are not deterred from pursuing educational and career goals.
A Priori v Post Hoc Testing
Authors: Berger Vance W. 
Published: September 2005

Abstract
In many situations, statistical analyses are given more credibility when they are planned prospectively, that is, in advance of the collection of the data. Such prespecified analyses cannot be said to have been suggested by the data, as post hoc analyses would be. A simple measure to prevent the difficult interpretation that can arise from post hoc analyses is to simply avoid them. This approach may be overly conservative, however, as the need may arise to test a hypothesis that the data suggested, and use the same data to test it. Several approaches exist for doing so, although not all of them have been cast as tests of post hoc analyses. In the analysis of variance framework, Fisher's least significant difference (LSD) and Scheffe's method can both be viewed as a means of performing post hoc linear comparisons, although they may not always be explicitly referred to as post hoc analyses. The Smirnov test may be viewed as a method to allow for the data to select the cut point of an ordinal outcome measure. Certain adaptive tests for ordinal data may be viewed as taking the Smirnov test to the next level, and allowing for the optimal combination of cut points, based on the data. The information‐preserving composite end point is a method to allow for data‐dependent outcome measure selection.
Age–Period–Cohort Analysis
Authors: Holford Theodore 
Published: September 2005

Abstract
When evaluating temporal trends, three perspectives to be considered are age, period and cohort. Age refers to chronological age of a subject when the outcome of interest occurs, and period the corresponding calendar date. Cohort refers to the year of birth, which identifies a generation, but this may be calculated by taking the difference between age and period, which can make these analyses difficult to interpret. Approaches for analyzing these temporal perspectives are described, including approaches to the identifiability problem that arises when one attempts to fit models that include all three temporal parameters at the same time. These methods are demonstrated using data on births per 1000 women among US blacks.
All‐
X
Models
Authors: Landis Ronald S. 
Published: September 2005

Abstract
All‐X models refer to applications of confirmatory factor analytic procedures in which the researcher treats all latent variables as exogenous. Model specification requires estimation of three sets of parameters including (a) loadings of measured variables on the underlying construct(s), (b) measurement errors associated with the observed variables, and (c) relationships, if any, between the latent exogenous constructs.
Allelic Association
Authors: Cardon Lon R. 
Published: September 2005

Abstract
Allelic association refers to the situation in which the distribution of a measured outcome (the trait) varies according to the distribution of one or more genetic variants (alleles). Associated alleles may be directly related to the trait in a causal or susceptibility relationship or may be indirectly related via intermediary markers. Association study designs often involve either cases and matched controls or small nuclear families. Studies of complex diseases have not met their anticipated success in the past, possibly because of small sample sizes and poor design for the small effect sizes that are becoming apparent for many traits. Current population‐based studies are underway that may help to identify new genetic loci for common diseases.
Alternating Treatments Design
Authors: Herrera Gina Coffee , Kratochwill Thomas R. 
Published: September 2005

Abstract
The alternating treatments design (ATD) is a type of single‐participant design that is commonly used to determine the effectiveness of two or more treatments. Conditions in the ATD are alternated rapidly and randomly/semirandomly, and effects can by analyzed statistically (e.g., randomization tests) and/or by visual inspection. Using the ATD can be advantageous because treatment effects can be found rather quickly and a withdrawal phase and baseline data are not required.
Incomplete Contingency Tables
Authors: Hershberger Scott L. 
Published: September 2005

AbstractIncomplete contingency tables have cells with no observations. When empty cells are predicted on the basis of theory or characteristics of the population, the cells have structural zeros. When empty cells occur from deficiencies in sampling, the cells have sampling zeros. While the analytic consequences of structural zeros are usually benign, the consequences arising from sampling zeros are often not so. The primary problem is deterioration in the accuracy of theG2and χ2approximations for testing the fit of loglinear models. Under these conditions, various strategies can be used to improve model testing.
Analysis of Variance
Authors: Serlin Ronald C. 
Published: September 2005

Abstract
The analysis of variance unites seemingly unrelated inferential methods into one exact procedure whose results can be reported in a single compact table. The analysis consists of partitioning the overall variability present in the data into parts reflecting the variability accounted for by explanatory factors and variability due to chance. If the amount of variability accounted for by an explanatory factor is enough larger than we would expect it to be simply due to the vagaries of random sampling, we conclude that there is a nonzero effect in the population due to the factor under examination. The analysis of variance allows a researcher to employ this logic while limiting the rate at which erroneous conclusions are drawn.
Analysis of Variance: Multiple Regression Approaches
Authors: Harris Richard J. 
Published: September 2005

Abstract

One‐way and factorial independent‐means analysis of variance (ANOVA) can be accomplished via a multiple regression analysis (MRA) in which the dependent variable is predicted from sets of level‐membership variables or, preferably, contrast variables representing the factors. Doing so can be useful in the two‐group design in that it provides an easily interpretable and often remarkably low estimate of the proportion of variance in the dependent variable, that is accounted for by an experimental manipulation. It also helps in the choice among alternative approaches to analyzing unequal‐
n
factorial designs by showing that full‐model analyses involve the comparison of unweighted means and that testing an effect uncorrected for any other effects implies making comparisons among weighted means. Furthermore, testing an effect corrected for confounds with some, but not all, other effects involves comparisons among the means that are difficult to characterize, require hand computations beyond those provided by ANOVA computer programs, and are unlikely to be of any real interest to the researcher. SPSS commands for carrying out factorial ANOVA via the MANOVA and REGRESSION commands are provided.
Ascertainment Corrections
Authors: Neale Michael C. 
Published: September 2005

AbstractAnalysis of data from non‐random samples of the population presents special challenges. Likelihood‐based methods offer a simple and direct way to correct statistical analysis by re‐normalizing the probability density function so that the probability of all possible outcomes sums to unity. The same approach may be applied to the analysis of continuous, binary or ordinal measures. Knowledge of the mechanism used to ascertain the sample is essential. Three types of ascertainment of pairs are considered for binary outcomes, according to whether the probability of being ascertained given affected status (π) is 1.0, almost zero, or intermediate. The last case, in which some concordant affected pairs are ascertained through both members of the pair, while others are ascertained through only one member, is the most challenging to implement.
Model Fit: Assessment of
Authors: Glas Cees A. W. 
Published: September 2005

Abstract
The fit of item response theory models can be evaluated by the computation of residuals and the associated test statistics. The procedures are targeted at three assumptions: the form of the item response curves, the assumption of local stochastic independence and the assumption of subpopulation invariance. A general statistical framework is given for the definition of test statistics with a know asymptotic distribution. The procedures are worked out in some detail for the 3‐parameter logistic model and the generalized partial credit model. Further, it is outlined how the procedures generalize to other parametric models for dichotomously and polytomously scored items. An example from a school effectiveness study serves as a small illustration. Finally, some references to alternative approaches to the evaluation of model if are given.
Test Dimensionality: Assessment of
Authors: Gessaroli Marc E. , de Champlain Andre F. 
Published: September 2005

Abstract
The ability to properly assess the dimensionality of a set of item responses is essential in psychometrics. Many popular psychometric methods using item response theory (IRT) such as item calibration and test equating assume that there is a single latent trait underlying the responses. As well, the popularity of multidimensional models has increased. Furthermore, test dimensionality is directly linked to the structural aspect of the construct validity of a test. History has shown some confusion in the definition of dimensionality and in the methods to assess it. Recent literature relates both the definition of dimensionality and its methods of assessment to the concepts of local independence and essential independence. This entry provides an overview of these definitions and of the more current methods of dimensionality assessment.
Assortative Mating
Authors: Hershberger Scott L. 
Published: September 2005

AbstractAssortative mating refers to nonrandom mating between individuals, and it can be based on observable characteristics of individuals, or characteristics of their environments, or both. Positive assortative mating is by far more common than negative assortative mating. If positive assortative mating is based on similarity of observable characteristics of individuals, the population genetic variance of the characteristic increases in the offspring generation. On the other hand, if positive assortative mating is based solely on environmental characteristics, genetic variance is unaffected. It is unlikely, however, that either mechanism of mate selection occurs in isolation for any single characteristic.
Attitude Scaling
Authors: Johnson Matthew S. , Junker Brian W. 
Published: September 2005

Abstract

Attitude scaling is the process of locating
J
attitude statements or items and/or
N
individuals on a latent continuum or scale. There are numerous methods available for the scaling of attitudes. The earliest methods, developed by L. L. Thurstone, R. Likert, and L. Guttman required two stages: One stage to locate the items on the scale and a second stage to locate the respondents. Other early work on the scaling of attitudes by C. H. Coombs allowed for the simultaneous estimation of both items and respondents, but the assumptions proved too restrictive for most real examples. Modern attitude scaling techniques use item response theory models, both monotone and unfolding, to perform attitude scaling.
Attrition
Authors: Shadish William R. , Luellen Jason K. 
Published: September 2005

Abstract
Attrition refers to a loss of response from study participants. Random attrition reduces statistical power but does not bias the results of a study. Systematic attrition reduces statistical power and can lead to generalizability biases and causal inference biases. For these reasons, it is best to prevent or minimize attrition. Attrition from measurement can and should be avoided even when attrition from treatment cannot be avoided. For attrition that cannot be prevented, a number of alternative strategies attempt to account for attrition during data analysis.
Free Response Data Scoring
Authors: Clauser Brian E. , Margolis Melissa J. 
Published: September 2005

Abstract
Computers offer the potential to extend assessment by delivering complex interactive item formats that require examinees to respond in ways that more closely approximate the ‘real world’ criterion behaviors of interest. However, for this expansion of assessment to be practically useful, it is necessary for the computer to both deliver and score the assessments. During the last two decades, these procedures have been the focus of considerable effort by numerous researchers. This entry describes the state of the art for computerized scoring of complex item formats. It begins with a presentation of the types of procedures currently in use. The entry then discusses the strengths and weaknesses of differing approaches, focusing on conceptual distinctions between approaches. The discussion concludes with comments about the future of automated scoring.
Axes in Multivariate Analysis
Authors: Krzanowski Wojtek J. 
Published: September 2005

AbstractQuantitative multivariate data can be represented geometrically as points in space, where the measured variables correspond to coordinate axes. Dimensionality reduction is effected by projecting the points into a subspace of this data space. Different projections highlight different features of the data. Some techniques produce linear combinations of the variables, and these linear combinations form the axes of the resultant subspace, while other techniques either find the subspace directly or implicitly. Consequences of these different possibilities are briefly discussed.
Balanced Incomplete Block Designs
Authors: Cotton John W. 
Published: September 2005

AbstractBalanced incomplete block designs (BIBD) are experimental designs that can be described by a labeled, fully filled rectangular array or by a larger equivalent rectangular display with some empty cells. A cell in the rectangle identifies one treatment in a given block. The number of different treatments for a given block (individual) is less than the total number of treatments; this precludes having each treatment appear once in every block. Hence, the design is anincompleteblock design. Without some constraints on the number of occurrences of certain treatments in different rows, the average performance in different parts of the design can be biased. This bias yields different averages for two treatments, for example, because of differences in the cells in which those treatments were employed. To eliminate the bias, a special form of balance is employed in which every possible pair of treatments appears in an equal number of blocks. Accordingly, there also is balance in the total number of times each treatment occurs. Analysis methods are discussed for general linear fixed, mixed, and Bayesian models. I discuss a special case of a BIBD design, Youden squares, that permits but does not require the assessment of one more independent variable than other BIBDs. In the behavioral sciences, the rows of Youden squares can be different blocks, typically different people or animals, and the columns can be different observation occasions that permit the assessment of so‐called period effects.
Item Response Theory (IRT) Models for Dichotomous Data
Authors: Hambleton Ronald K. , Zhao Yue 
Published: September 2005

AbstractThis entry provides an introduction to the topic of item response theory. Shortcomings of classical test models are considered first. Second, current item response models for the analysis of dichotomously scored item response data are introduced. Estimation of model parameters, assessment of model fit, and available software, are described next. Finally, applications of item response theory IRT models to test development, item bias, equating, and computer‐adaptive testing are briefly described.
Battery Reduction
Authors: Massaro Joseph M. 
Published: September 2005

Abstract

Battery reduction is used to select a subset of
m
variables from an original set of
n
variables (
m
<
n
) that reproduce a large proportion of the variance in the original set of
n
variables. There are a number of procedures for performing battery reduction analysis. A popular method involves performing a principal components analysis first to select
m
components, which account for the salient variance in the original data. Gram–Schmidt orthogonal rotations are then performed to determine the
m
variables that account for the largest proportion of variance. The procedure is illustrated and reference made to a SAS macro for performing the analysis.
Bayesian Item Response Theory Estimation
Authors: Swaminathan Hariharan 
Published: September 2005

AbstractThe problem of fundamental importance in item response theory is the accurate estimation of the parameters that characterize the items and the ability or the proficiency levels of examinees. While in general, likelihood‐based approaches such as joint, conditional, and marginal maximum likelihood procedures provide reasonable estimates of the item parameters, more often than not these procedures yield estimates in the two‐ and three‐parameter models that are inadmissible in the sense that the estimates of the ability and item parameters fall outside acceptable ranges. Bayesian approaches, by taking into account prior and collateral information, overcome the problems encountered by likelihood‐based approaches.
Bayesian Methods for Categorical Data
Authors: Gutiérrez‐Peña Eduardo 
Published: September 2005

AbstractThe Bayesian approach to statistical inference is based on a subjective interpretation of probability. Given a prior distribution describing our prior beliefs concerning the value of an unknown quantity, Bayes' theorem allows us to update those beliefs in the light of observed data. The resulting posterior distribution then summarizes all the available information about the quantity of interest, conditional on the posited model. Bayesian methods for the analysis of categorical data use the same classes of models as the classical approach. However, Bayesian analyses can be more informative – the posterior distribution of the parameter contains more information than mere point estimates or test statistics – and may provide more natural solutions in certain situations such as those involving sparse or missing data, or unidentifiable parameters.