TouchStat: A Monte Carlo program for calculating sequential touching probabilities

A growing number of child cognition researchers are using an object-manipulation, sequential-touching paradigm to explore young children’s conceptual abilities. Within this paradigm, it is essential to distinguish children’s intracategory touching sequences from those expected by chance. The sequentialtouching approach is congruent with a permutation testing model of statistical inference and is best modeled by sampled permutations as derived from Monte Carlo procedures. In this article, we introduce a computer program for generating Monte Carlo sequential-touching simulations. TouchStat permits users to determine their own specifications to simulate sequential touching to category exemplars across a wide range of task parameters. We also present Monte Carlo chance probabilities for the standard two-category, four-exemplar task, with sequences up to 30 touches long. Finally, we consider broader applications of the TouchStat program.     

Software for advanced ANOVA courses: A survey

In response to a survey of faculty regarding their commercial software preferences for advanced analysis of variance courses, it was found that the most frequently used packages were SAS, SPSS^x, and BMDP, all originally mainframe packages. The fourth choice, SYSTAT, was written for microcomputers but is currently also available for other host computers. Difficulty for students was the most frequently cited reason fornot using one of these four packages. The most important criteria for choosing software packages were variety of designs, accuracy, and ease of use. Cost was a factor only for microcomputer licenses. Packages using the general linear model approach were paramount to some, while others would not consider such packages. Instructors decried the lack of the “ideal program,” but the diversity of their desires makes it clear that no program could be ideal for all of them. Many faculty seemed unaware of newer software packages or of the extent to which older packages (particularly Minitab) have been modified; some had their choices constrained by departmental limitations. Better dissemination of information about statistical software is needed, whether it be from software publishers or through the professional literature.     

INFOBITS: A Visual Basic program for calculating information theoretic statistics from behavior sequences

We describe a Visual Basic add-in macro program for Microsoft Excel 5 and 7 (and later versions) that calculates basic, first-order, information theoretic statistics from matrices based on behavior sequences, such as those from animal or human interaction studies. Information theoretic statistics measure association between behavioral events in bits, a unit that is independent of the particular system under study. A sample size bias correction of the value for the mean information transmission (Ht) is included in the program. A normalization of Ht reports the efficiency of information transmission relative to the amount of information in the system. The program incorporates an iterative pseudo-random resampling algorithm that reports a confidence level (P) for Ht. Mean information transmission is partialized, to determine the relative contribution of each behavior category to Ht. An algorithm for calculating confidence intervals allows comparison among different matrices. The program runs in a common spreadsheet, and is therefore useful to researchers or students who only have access to desktop or laptop microcomputers.     

HMMTree: A computer program for latent-class hierarchical multinomial processing tree models

Latent-class hierarchical multinomial models are an important extension of the widely used family of multinomial processing tree models, in that they allow for testing the parameter homogeneity assumption and provide a framework for modeling parameter heterogeneity. In this article, the computer program HMMTree is introduced as a means of implementing latent-class hierarchical multinomial processing tree models. HMMTree computes parameter estimates, confidence intervals, and goodness-of-fit statistics for such models, as well as the Fisher information, expected category means and variances, and posterior probabilities for class membership. A brief guide to using the program is provided.     

Interaction in ANOVA: misconceptions

Although interaction in analysis of variance has an unequivocal theoretical meaning (and so it appears in the statistic literature), frequent misconceptions are found in empirical research, which, in many cases, lead to wrong conclusions. In this paper, 150 articles are reviewed: in 12.7% of them, no attention is paid to the interaction (either because it is not analysed or because it is analysed but not discussed); in 79.1%, interaction is studied through simple effects analysis; and only in 8.2% of the cases, interaction is correctly discussed. It could be that psychology researchers tend to analyse and interpret the interaction between factors incorrectly because the most widespread statistic packages (with SPSS in the lead) do not allow performing the comparisons needed to analyse a significant interaction in factorial designs with randomized groups. In order to contribute to eradicating this problem, we herein show how to design some of the linear comparisons that allow isolating the interaction effect, and we explain how to use SPSS to compute these comparisons.