非正态分布下概化理论方差分量变异量估计

方差分量估计是概化理论的必用技术,但受限于抽样,需要对其变异量进行探讨。采用Monte Carlo数据模拟技术,探讨非正态数据分布对四种方法估计概化理论方差分量变异量的影响。结果表明：（1）不同非正态数据分布下,各种估计方法的“性能”表现出差异性;（2）数据分布对方差分量变异量估计有影响,适合于非正态分布数据的方差分量变异量估计方法不一定适合于正态分布数据。     

Comparing one-step m-estimators of location corresponding to two independent groups

Experience with real data indicates that psychometric measures often have heavy-tailed distributions. This is known to be a serious problem when comparing the means of two independent groups because heavy-tailed distributions can have a serious effect on power. Another problem that is common in some areas is outliers. This paper suggests an approach to these problems based on the one-step M-estimator of location. Simulations indicate that the new procedure provides very good control over the probability of a Type I error even when distributions are skewed, have different shapes, and the variances are unequal. Moreover, the new procedure has considerably more power than Welch's method when distributions have heavy tails, and it compares well to Yuen's method for comparing trimmed means. Wilcox's median procedure has about the same power as the proposed procedure, but Wilcox's method is based on a statistic that has a finite sample breakdown point of only 1/n, wheren is the sample size. Comments on other methods for comparing groups are also included.     

A modified procedure for parallel analysis of ordered categorical data

Parallel analysis has been well documented to be an effective and accurate method for determining the number of factors to retain in exploratory factor analysis. The O'Connor (2000) procedure for parallel analysis has many benefits and is widely applied, yet it has a few shortcomings in dealing with missing data and ordinal variables. To address these technical issues, we adapted and modified the O'Connor procedure to provide an alternative method that better approximates the ordinal data by factoring in the frequency distributions of the variables (e.g., the number of response categories and the frequency of each response category per variable). The theoretical and practical differences between the modified procedure and the O'Connor procedure are discussed. The SAS syntax for implementing this modified procedure is also provided.     

A Proposed Number Correct Scoring Procedure Based on Classical True-Score Theory and Multidimensional Item Response Theory

A hybrid procedure for number correct scoring is proposed. The proposed scoring procedure is based on both classical true-score theory (CTT) and multidimensional item response theory (MIRT). Specifically, the hybrid scoring procedure uses test item weights based on MIRT and the total test scores are computed based on CTT. Thus, what makes the hybrid scoring method attractive is that this method accounts for the dimensionality of the test items while test scores remain easy to compute. Further, the hybrid scoring does not require large sample sizes once the item parameters are known. Monte Carlo techniques were used to compare and contrast the proposed hybrid scoring method with three other scoring procedures. Results indicated that all scoring methods in this study generated estimated and true scores that were highly correlated. However, the hybrid scoring procedure had significantly smaller error variances between the estimated and true scores relative to the other procedures.     

反应风格的测量与统计控制

反应风格是共同方法偏差的主要来源之一。本文首先讨论反应风格的定义和类型,梳理其危害,认为反应风格能使测验分数出现偏差,影响测验信效度分析和变量关系分析,有必要控制其危害。然后介绍了常用的反应风格测量方法,包括计数法和模型法两大类,对测量方法的选择给出了建议,在此基础上,就如何结合反应风格的测量方法与残差回归法、偏相关法来控制反应风格危害给出建议。     

反应风格的测量与统计控制

反应风格是共同方法偏差的主要来源之一。本文首先讨论反应风格的定义和类型,梳理其危害,认为反应风格能使测验分数出现偏差,影响测验信效度分析和变量关系分析,有必要控制其危害。然后介绍了常用的反应风格测量方法,包括计数法和模型法两大类,对测量方法的选择给出了建议,在此基础上,就如何结合反应风格的测量方法与残差回归法、偏相关法来控制反应风格危害给出建议。     

The discrimination of two racial samples

Nineteen different anthropometric measures were obtained on all members of each of two racial groups. A procedure was developed and applied to the data to give maximum differentiation between the groups. The method is applicable wherever we have a large number of independent variables and a dependent variable. In such cases, the conventional methods for determining multiple regression constants are very laborious. An iteration method is presented which is more rapid than any with which the writers are familiar. The method selects in sequence those variables which together yield the largest multiple correlation with the criterion. At each step in the procedure, rapid estimates of the regression weights and the multiple correlation at that point are available.     

The application and utility of a family assessment procedure in a child psychiatry clinic

The application of a method of assessing families from a total family systems viewpoint is explored. It was found that the method (the McMaster Model) was well-suited to routine practice in a British child psychiatry setting with routine clinic referrals. It constituted a good procedure both for assessing and for preparing families for family therapy. In this paper the practical procedure is described. Some of the issues arising from the approach and from the assessment of thirty-four clinic families are discussed. It was also found that the method provided a very good framework for teaching.     

Item selection by means of a maximizing function

A new item selection technique is presented which takes into account the intercorrelations of the items as well as their correlations with the criterion. The technique is regarded as superior to comparable techniques in that it is considered to achieve greater economy of time, greater objectivity of procedure, higher validity, and higher reliability. The mathematical theory underlying the method is developed. An approximate solution of the mathematical equations is suggested. An approximation procedure for the complete item selection technique is presented, based on the mathematical solution, but much simpler in procedure. The clerical operations involved in the approximation procedure are outlined and illustrated on a sample worksheet.     

Process dissociation using a guided procedure

A method for achieving process dissociation is described that places less emphasis on participants' understanding and remembering interpretations of test cues than does the standard procedure. The proposed method, called the guided procedure, tests memory with a sequence of two prompts, one requesting word-stem recognition, followed by another for word-stem completion. Inclusion and exclusion conditions are produced by requesting completion of recognized stems to form previously presented or new words, respectively. Estimates of automatic and conscious memory produced by the standard and the guided procedures are compared in studies modeled after Toth, Reingold, and Jacoby (1994). Although not significantly different in many aspects, the outcomes differ in ways that may reflect less reliance on a generate-recognize strategy of participants tested with the guided procedure. Additional measures of memory available only with the guided procedure are presented.     

Some statistical treatments compatible with individual organism methodology

Consider experimental treatments with consequences so irreversible that baseline performance cannot be recovered. The conventional method of assessing the effects of such treatments by statistical means involves separate experimental and control groups. An alternative proposed here is to administer the experimental treatment to each subject, one subject at a time and in a random order; whenever any subject receives the experimental treatment, those subjects which have not yet received it receive a control treatment. This procedure permits results significant at the one-tailed 0.05 level to be obtained with four subjects; if a two-group procedure evaluated by means of the U test is used, a minimum of six subjects is needed for the same significance level. More generally, the procedure permits equal sensitivity to any experimental effect with over 30% fewer subjects than a two-group procedure. Extensions of the basic method are made to a variety of levels of the experimental treatment and to treatments without irreversible effects, and limitations of the method are discussed.     

Goal attainment scaling: An idiosyncratic method to assess treatment effectiveness in agoraphobia

Goal attainment scaling (GAS) is an individually tailored way to measure treatment gains, using a highly standardized procedure. An advantage of the method is that it takes into account individual characteristics of the patients, and at the same time the data are suitable for quantitative analysis and comparable across patients. Despite the wide acceptance and use of the method in the evaluation of psychotherapy, data on its psychometric properties are rather scarce. In the current study, GAS was used as one of several outcome measures in a research project on the effectiveness of various treatments for panic disorder with agoraphobia. Guidelines for GAS are presented as well as data on the reliability and validity of the procedure. Results indicate that the procedure is reliable, valid, and sensitive to the improvement of patients during treatment. Comparison of GAS with standardized measures revealed considerable concordance, although the clinical end status of patients diverged somewhat dependent on the measure considered.     

An iterative procedure for extracting skill maps from data

The methodologies for the construction of a knowledge structure mainly refer to the query to experts, the skill maps, and the data-driven approaches. This last method is of growing interest in recent literature. In this paper, an iterative procedure for building a skill map from a set of data is introduced. This procedure is based on the minimization of the distance between the knowledge structure delineated by a given skill map and the data. The accuracy of the proposed method is tested through a number of simulation studies where the amount of noise in the data is manipulated as well as the kind of structure to be reconstructed. Results show that the procedure is accurate and that its performance tends to be sufficiently stable even with high error rates. The procedure is compared to two already-existing methodologies to derive knowledge structures from a set of data. The use of the corrected Akaike Information Criterion (AICc) as a stopping criterion of the iterative reconstruction procedure is tested against the app criterion introduced by Schrepp. Moreover, two empirical applications on clinical data are reported, and their results show the applicability of the procedure.     

A comparison of methods for teaching receptive labeling to children with autism spectrum disorders

Many early intervention curricular manuals recommend teaching auditory-visual conditional discriminations (i.e., receptive labeling) using the simple-conditional method in which component simple discriminations are taught in isolation and in the presence of a distracter stimulus before the learner is required to respond conditionally. Some have argued that this procedure might be susceptible to faulty stimulus control such as stimulus overselectivity (Green, 2001). Consequently, there has been a call for the use of alternative teaching procedures such as the conditional-only method, which involves conditional discrimination training from the onset of intervention. The purpose of the present study was to compare the simple-conditional and conditional-only methods for teaching receptive labeling to 3 young children diagnosed with autism spectrum disorders. The data indicated that the conditional-only method was a more reliable and efficient teaching procedure. In addition, several error patterns emerged during training using the simple-conditional method. The implications of the results with respect to current teaching practices in early intervention programs are discussed.     

The mean and variance of the selection differential after top‐down selection from a mixture of normal samples

A procedure is presented for determining the mean and variance of the selection differential for top‐down selections in which the candidates come from populations that have a different average score on the selection measure. Although the procedure is based on the same stochastic model and requires identical data to the currently available method for estimating the mean selection differential, it has the advantage that the resulting expressions are valid for finite‐sample selection decisions and that the variance of the selection differential can also be assessed. The difference between the two procedures is illustrated by means of an example application, and it is shown how the present results are particularly helpful in determining the expected utility of personnel selection decisions.     

THE LAW OF CATEGORICAL JUDGMENT AND THE MEASUREMENT OF COLOR CONSTANCY

The scaling method used by von Fieandt, Ahonen & Järvinen (1964) for measuring color constancy is discussed. It is argued that (i) the underlying scaling model and the experimental procedure they employed are incompatible, and that (ii) the analytical procedure they applied to the data for obtaining the empirical scale values is incorrect. The data are reanalyzed, and the goodness of fit of both the original and the present results is evaluated.     

Fast and accurate measurement of taste and smell thresholds using a maximum-likelihood adaptive staircase procedure

This paper evaluates the use of a maximum-likelihood adaptive staircase psychophysical procedure (ML-PEST), originally developed in vision and audition, for measuring detection thresholds in gustation and olfaction. The basis for the psychophysical measurement of thresholds with the ML-PEST procedure is developed. Then, two experiments and four simulations are reported. In the first experiment, ML-PEST was compared with the Wetherill and Levitt up-down staircase method and with the Cain ascending method of limits in the measurement of butyl alcohol thresholds. The four Monte Carlo simulations compared the three psychophysical procedures. In the second experiment, the test-retest reliability of ML-PEST for measuring NaCl and butyl alcohol thresholds was assessed. The results indicate that the ML-PEST method gives reliable and precise threshold measurements. Its ability to detect malingerers shows considerable promise. It is recommended for use in clinical testing.     

Fast and accurate measurement of taste and smell thresholds using a maximum-likelihood adaptive staircase procedure.

This paper evaluates the use of a maximum-likelihood adaptive staircase psychophysical procedure (ML-PEST), originally developed in vision and audition, for measuring detection thresholds in gustation and olfaction. The basis for the psychophysical measurement of thresholds with the ML-PEST procedure is developed. Then, two experiments and four simulations are reported. In the first experiment, ML-PEST was compared with the Wetherill and Levitt up-down staircase method and with the Cain ascending method of limits in the measurement of butyl alcohol thresholds. The four Monte Carlo simulations compared the three psychophysical procedures. In the second experiment, the test-retest reliability of MLPEST for measuring NaCl and butyl alcohol thresholds was assessed. The results indicate that the ML-PEST method gives reliable and precise threshold measurements. Its ability to detect malingerers shows considerable promise. It is recommended for use in clinical testing.     

Controlling item exposure and test overlap on the fly in computerized adaptive testing

This paper proposes an on‐line version of the Sympson and Hetter procedure with test overlap control (SHT) that can provide item exposure control at both the item and test levels on the fly without iterative simulations. The on‐line procedure is similar to the SHT procedure in that exposure parameters are used for simultaneous control of item exposure rates and test overlap rate. The exposure parameters for the on‐line procedure, however, are updated sequentially on the fly, rather than through iterative simulations conducted prior to operational computerized adaptive tests (CATs). Unlike the SHT procedure, the on‐line version can control item exposure rate and test overlap rate without time‐consuming iterative simulations even when item pools or examinee populations have been changed. Moreover, the on‐line procedure was found to perform better than the SHT procedure in controlling item exposure and test overlap for examinees who take tests earlier. Compared with two other on‐line alternatives, this proposed on‐line method provided the best all‐around test security control. Thus, it would be an efficient procedure for controlling item exposure and test overlap in CATs.     

Using the Bollen-Stine Bootstrapping Method for Evaluating Approximate Fit Indices

Accepting that a model will not exactly fit any empirical data, global approximate fit indices quantify the degree of misfit. Recent research (Chen, Curran, Bollen, Kirby, & Paxton, 2008) has shown that using fixed conventional cut-points for approximate fit indices can lead to decision errors. Instead of using fixed cut points for evaluating approximate fit indices, this study focuses on the meaning of approximate fit and introduces a new method to evaluate approximate fit indices. Millsap (2012) introduced a simulation-based method to evaluate approximate fit indices. A limitation of Millsap's (2012) work was that a rather strong assumption of multivariate normality was implied in generating simulation data. In this study, the Bollen-Stine bootstrapping procedure (Bollen & Stine, 1993) is proposed to supplement the former study. When data are nonnormal, the conclusions derived from Millsap's (2012) simulation method and the Bollen-Stine method can differ. Examples are given to illustrate the use of the Bollen-Stine bootstrapping procedure for evaluating the Root Mean Squared Error of Approximation (RMSEA). Comparisons are made with the simulation method. The results are discussed, and suggestions are given for the use of proposed method.