A Modest Solution to the Problem of Rule-following

A modest solution to the problem(s) of rule-following is defended against Kripkensteinian scepticism about meaning. Even though parts of it generalise to other concepts, the theory as a whole applies to response-dependent concepts only. It is argued that the finiteness problem is not nearly as pressing for such concepts as it may be for some other kinds of concepts. Furthermore, the modest theory uses a notion of justification as sensitivity to countervailing conditions in order to solve the justification problem. Finally, in order to solve the normativity problem, it relies on substantial specifications of normal conditions such as those that have been proposed by Crispin Wright and Mark Johnston, rather than on Philip Pettit's functionalist specification. This theory is modest in that it does not meet the demands of Kripke's sceptic in full. Arguments are provided as to why this is not needed.     

Tests of homogeneity of means and covariance matrices for multivariate incomplete data

Existing test statistics for assessing whether incomplete data represent a missing completely at random sample from a single population are based on a normal likelihood rationale and effectively test for homogeneity of means and covariances across missing data patterns. The likelihood approach cannot be implemented adequately if a pattern of missing data contains very few subjects. A generalized least squares rationale is used to develop parallel tests that are expected to be more stable in small samples. Three factors were varied for a simulation: number of variables, percent missing completely at random, and sample size. One thousand data sets were simulated for each condition. The generalized least squares test of homogeneity of means performed close to an ideal Type I error rate for most of the conditions. The generalized least squares test of homogeneity of covariance matrices and a combined test performed quite well also.Preliminary results on this research were presented at the 1999 Western Psychological Association convention, Irvine, CA, and in the UCLA Statistics Preprint No. 265 (http://www.stat.ucla.edu). The assistance of Ke-Hai Yuan and several anonymous reviewers is gratefully acknowledged.     

On robusiness of the normal-theory based asymptotic distributions of three reliability coefficient estimates

This paper studies the asymptotic distributions of three reliability coefficient estimates: Sample coefficient alpha, the reliability estimate of a composite score following a factor analysis, and the estimate of the maximal reliability of a linear combination of item scores following a factor analysis. Results indicate that the asymptotic distribution for each of the coefficient estimates, obtained based on a normal sampling distribution, is still valid within a large class of nonnormal distributions. Therefore, a formula for calculating the standard error of the sample coefficient alpha, recently obtained by van Zyl, Neudecker and Nel, applies to other reliability coefficients and can still be used even with skewed and kurtotic data such as are typical in the social and behavioral sciences.This research was supported by grants DA01070 and DA00017 from the National Institute on Drug Abuse and a University of North Texas faculty research grant. We would like to thank the Associate Editor and two reviewers for suggestions that helped to improve the paper.     

高等师范生成就动机取向特点的研究

本文以120名在校大学生为研究对象,分析了高等师范生的成就动机取向的特点。研究结果表明：1、高师生的个我取向成就动机明显高于社会取向成就动机;2、高师生成就动机取向的性别差异不明显;3、不同文化背景(城市与农村)学生的成就动机取向无明显差异;4、不同年级学生的成就动机取向无明显差异。     

Reproductive ectogenesis: The third era of human reproduction and some moral consequences

In a well known story Derek Parfit describes a disconnection between two entities that normally (in real life) travel together through space and time, namely your personal identity consisting of both mind and body. Realising the possibility of separation, even if it might never happen in real life, new questions arise that cast doubt on old solutions. In human reproduction, in real life, at present the fetus spends approximately nine months inside the pregnant woman. But, we might envisage other possibilities. Historically, the first era is the normal conception inside the woman, the growth of the fetus in the womb and then, after nine months, birth and the appearance of a new individual. The second era is In Vitro Fertilisation (IVF). The fetus starts outside the woman as a fertilised egg, moves to the body of the woman and spends nine month there, where the body of the woman and the fetus travel together in space-time to separate at birth. In the third era of reproductive ectogenesis, the two never travel together. The fetus spends its gestational time entirely outside the woman’s body. We have two entities separated in space-time the whole time. The intimate connection consisting in the fetus being a part of the woman’s body is gone. In this paper I will briefly comment on the three eras of human reproduction — and primarily on the relationship between the new individual and the woman — and then spend some time with a fictional story illustrating some moral consequences of the third era. The story is from Pig Pharmaceuticals Limited and how they in the year 2050 report the successful development of pig-related pregnancies with transgenic pigs as surrogate mothers.     

Bayesian modeling of measurement error in predictor variables using item response theory

It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between the latent variables and dichotomous observed variables, which may be responses to tests or questionnaires. It will be shown that the multilevel model with measurement error in the observed predictor variables can be estimated in a Bayesian framework using Gibbs sampling. In this article, handling measurement error via the normal ogive model is compared with alternative approaches using the classical true score model. Examples using real data are given.This paper is part of the dissertation by Fox (2001) that won the 2002 Psychometric Society Dissertation Award.     

A rasch model for continuous ratings

A unidimensional latent trait model for continuous ratings is developed. This model is an extension of Andrich's rating formulation which assumes that the response process at latent thresholds is governed by the dichotomous Rasch model. Item characteristic functions and information functions are used to illustrate that the model takes ceiling and floor effects into account. Both the dichotomous Rasch model and a linear model with normally distributed error can be derived as limiting cases. The separability of the structural and incidental parameters is demonstrated and a procedure for estimating the parameters is outlined.     

Modelling non‐normal data: The relationship between the skew‐normal factor model and the quadratic factor model

Maximum likelihood estimation of the linear factor model for continuous items assumes normally distributed item scores. We consider deviations from normality by means of a skew‐normally distributed factor model or a quadratic factor model. We show that the item distributions under a skew‐normal factor are equivalent to those under a quadratic model up to third‐order moments. The reverse only holds if the quadratic loadings are equal to each other and within certain bounds. We illustrate that observed data which follow any skew‐normal factor model can be so well approximated with the quadratic factor model that the models are empirically indistinguishable, and that the reverse does not hold in general. The choice between the two models to account for deviations of normality is illustrated by an empirical example from clinical psychology.     

Extending sequence-class membership with matching to sample

Three normal adults were first trained to point sequentially to each member of several pairs of visual stimuli. This baseline training established one class of stimuli to which subjects responded first, and another class of stimuli to which they responded second. Then, in a matching-to-sample procedure, baseline-sequence stimuli served as samples and new visual stimuli served as comparisons. Subjects were trained to choose one group of new comparisons when the sample was a "first" stimulus from the sequence baseline, and to choose the other new comparison stimuli when the sample was a "second" from the sequence baseline. When the new stimuli were then presented as pairs in the posttest, two subjects pointed to them in sequences predictable on the basis of the stimulus-class membership established during matching to sample. The failure of one subject to demonstrate sequential transfer was shown to be a consequence of the failure of the matching-to-sample procedure to establish stimulus classes. The production of sequences that were not directly trained suggested an empirical approach to the analysis of simple grammatical behavior.