A monte carlo investigation of recovery of structure by alscal

A Monte Carlo study was carried out to investigate the ability of ALSCAL to recover true structure inherent in simulated proximity measures. The nature of the simulated data varied according to (a) number of stimuli, (b) number of individuals, (c) number of dimensions, and (d) level of random error. Four aspects of recovery were studied: (a) SSTRESS, (b) recovery of true distances, (c) recovery of stimulus dimensions, and (d) recovery of individual weights. Results indicated that all four measures were rather strongly affected by random error. Also, SSTRESS improved with fewer stimuli in more dimensions, but the other three indices behaved in the opposite fashion. Most importantly, it was found that the number of individuals, over the range studied, did not have a substantial effect on any of the four measures of recovery. Practical implications and suggestions for further research are discussed.The authors wish to thank Drs. Forrest W. Young, Paul D. Isaac and Thomas E. Nygren, who provided many helpful comments during this project.     

A comparison of severalk sample tests for ordered alternatives in completely randomized designs

The importance of appropriate test selection for a given research endeavor cannot be over-emphasized. Using samples drawn from eleven populations (differing in shape, peakedness, and density in the tails), this study investigates the small sample empirical powers of ninek-sample tests against ordered location alternatives under completely randomized designs. The results then are intended to aid the researcher in the selection of a particular procedure appropriate for a given endeavor. To highlight this an industrial psychology application involving work productivity is presented.Research was supported in part by the Scholastic Assistance Program, Baruch College. The author wishes to thank Professors Matthew Goldstein, Shulamith Gross, David Levine, and Edward Wolf for their helpful comments when writing this paper. In addition, the author wishes to thank the referees and editor for their useful suggestions for improving the paper.     

Statistical evaluation of measures of fit in the Lingoes-Borg procrustean individual differences scaling

PINDIS, as recently presented by Lingoes and Borg [1978] not only marks the latest development within the scope of individual differences scaling, but, may be of benefit in some closely related topics, such as target analysis. Decisions on whether the various models available from PINDIS fit fallible data are relatively arbitrary, however, since a statistical theory of the fit measures is lacking. Using Monte Carlo simulation, expected fit measures as well as some related statistics were therefore obtained by scaling sets of 4(4)24 random configurations of 5(5)30 objects in 2, 3, and 4 dimensions (individual differences case) and by fitting one random configuration to a fixed random target for 5(5)30 objects in 2, 3, and 4 dimensions (target analysis case). Applications are presented.     

On testing the equality of proportions in the paired case with incomplete data

The problem of testing two correlated proportions with incomplete data is considered by means of Monte Carlo simulations studies. A test proposed in this paper, which can be regarded as a generalization of McNemar's test, is recommended in all cases with incomplete data and not too small samples.     

An INAR(1) negative multinomial regression model for longitudinal count data

This paper discusses a regression model for the analysis of longitudinal count data observed in a panel study. An integer-valued first-order autoregressive [INAR(1)] Poisson process is adapted to represent time-dependent correlations among the counts. By combining the INAR(1)-representation with a random effects approach, a new negative multinomial distribution is derived that includes the bivariate negative binomial distribution proposed by Edwards and Gurland (1961) and Subrahmaniam (1966) as a special case. A detailed analysis of the relationship between personality factors and daily emotion experiences illustrates the approach.This research was partially supported by NSF grant SBR-9409531. The author is grateful to Ulrich Schimmack and Ed Diener for providing the data set used in the application section and for helpful comments on this research.     

A study of the classification capabilities of neural networks using unsupervised learning: A comparison withK-means clustering

Several neural networks have been proposed in the general literature for pattern recognition and clustering, but little empirical comparison with traditional methods has been done. The results reported here compare neural networks using Kohonen learning with a traditional clustering method (K-means) in an experimental design using simulated data with known cluster solutions. Two types of neural networks were examined, both of which used unsupervised learning to perform the clustering. One used Kohonen learning with a conscience and the other used Kohonen learning without a conscience mechanism. The performance of these nets was examined with respect to changes in the number of attributes, the number of clusters, and the amount of error in the data. Generally, theK-means procedure had fewer points misclassified while the classification accuracy of neural networks worsened as the number of clusters in the data increased from two to five.Acknowledgements: Sara Dickson, Vidya Nair, and Beth Means assisted with the neural network analyses.     

Molecular carrier testing for the fragile X syndrome: Issues for genetic counselors

Molecular analysis of the fragile X (FMR-1) gene identifies female fragile X carriers, but appropriate genetic counseling can only be provided if the limitations of the testing methods are understood. Molecular analysis of this gene is achieved with both the polymerase chain reaction (PCR) and Southern blot techniques. PCR is faster and can determine the actual number of CGG repeats, which modifies genetic counseling substantially. However, for a sizeable percentage of women, PCR alone is not conclusive, and Southern analysis is necessary to complete the study. While this procedure takes longer, it is usually conclusive. Women who present for genetic counseling and carrier testing in the second trimester of pregnancy need this information quickly, and for them the turn-around time is paramount. It is critical that genetic counselors understand these methods so that they can educate their clients and facilitate appropriate follow-up.     

Enumeration and simulation methods for 0–1 matrices with given marginals

Data in the form of zero-one matrices where conditioning on the marginals is relevant arise in diverse fields such as social networks and ecology; directed graphs constitute an important special case. An algorithm is given for the complete enumeration of the family of all zero-one matrices with given marginals and with a prespecified set of cells with structural zero entries. Complete enumeration is computationally feasible only for relatively small matrices. Therefore, a more useable Monte Carlo simulation method for the uniform distribution over this family is given, based on unequal probability sampling and ratio estimation. This method is applied to testing reciprocity of choices in social networks.The author wishes to thank Cajo ter Braak and John Birks for pointing out the relevance of this subject for ecology; and also Albert Verbeek and Ivo Molenaar, a referee, the Editor, and the Associate Editor for their comments. An earlier version of this paper was presented at the Stockholm Conference on Random Graphs and Applications (April 25–27, 1989), organized with financial support from the Swedish Council of Research in the Humanities and the Social Sciences.     

GPCM模型项目参数估计程序的开发与研究

该文对GPCM的项目参数估计的方法进行较为深入的探讨,特别对容易混淆的参数初值计算以及项目参数分两步进行估计的原因进行了阐述。并且基于MMLE／EM算法,开发了相应的项目参数估计程序。通过大量的蒙特卡洛模拟,与国外专业软件PARSCALE比较,本程序的步骤参数估计值更好,区分度参数估计值相当,具有较好的应用价值。     

Intervention Effects on Stage of Change Membership and Transitions among Adolescent Energy Balance Behaviors

The transition from childhood to adolescence is a crucial period for the development of healthy behaviors to be sustained later in life. With obesity a leading public health problem, the promotion of healthy behaviors has the potential to make a huge impact. The current study evaluated Stage of Change progression in a large (N = 4158) computer-delivered, Transtheoretical Model-tailored intervention focusing on physical activity and fruit and vegetable consumption (FV). Markov models were used to explore stage transitions and patterns of discrete change from sixth to ninth grade. Nested model comparisons examined the consistency of these patterns across time and intervention condition. Major findings supported models in which participants were free to transition forward and backward to any of the stages, but higher probabilities were observed for remaining in the same stage or for transitioning one or two stages forward. Participants in the intervention group had higher probabilities of transitioning toward Maintenance, with more change occurring relative to the comparison group during transitions from grades six to eight but not for grades eight to nine.