A comparison of inexpensive statistical packages for microcomputers running MS-DOS

The purpose of the present paper is to describe and compare some inexpensive software packages that calculate a variety of statistics on microcomputers running MS-DOS. For each package, hardware requirements, program capabilities, limitations, accuracy, error handling, and other features are considered.     

Writing high-quality statistical software for Apple II microcomputers

The purpose of this paper is to describe some principles and techniques that programmers should consider when trying to improve or create a statistical package. Four computational issues are discussed: accuracy, speed, computing probabilities, and error trapping. A single-array data structure is proposed for use within the program. Several other input-output issues are covered, including menus, command languages, questions, data input and editing, CRT and printer formatting, and graphics.     

Survey of integrated statistical computer packages

The statistical features and general characteristics of seven integrated packages were surveyed. SPSS, DATA-TEXT, and OSIRIS emerged as the most comprehensive. OSIRIS in particular offered the most extensive multivariate analysis capabilities. The only category of statistical analysis neglected in all of the packages was nonparametric procedures related to ordinal data. Information on availability and user’s manuals is provided.     

A comparison of two multicomponent treatment packages for food refusal

Food refusal is a severe feeding problem in which children refuse to eat all or most foods, which can be treated effectively using multicomponent intervention packages. This study compared two multicomponent treatment packages on food and drink consumption, inappropriate mealtime behavior, and total intake in a child with food refusal. Bite and drink consumption was consistently higher; inappropriate mealtime behavior was consistently lower; and total intake was greater when differential reinforcement of alternative behavior and escape extinction treatment were implemented compared to response cost, escape extinction, and differential reinforcement of alternative behavior.     

The equivalence of three statistical packages for performing hierarchical cluster analysis

Three different software programs which contain hierarchical agglomerative cluster analysis procedures were shown to generate different solutions on the same data set using apparently the same options. The basis for the differences in the solutions was the formulae used to calculate Euclidean distance. Users of statistical software were warned of terminological confusion concerning cluster analysis.This research was supported by a National Science Foundation grant (DCR#74-20007) entitled A Consumer Report on Cluster Analysis Software. I wish to thank the authors of the three programs for their helpful comments on the paper.     

A bit-addressable I/O interface for microcomputers

An input/output (I/O) interface design based on the 6522 VIA is described. This design is enhanced with additional circuitry to provide such features as latched input, bit-addressable I/O line control, and provisions for expansion.     

A versatile memory-mapped I/O interface for microcomputers

An inexpensive and easy-to-bulid input/output interface capable of driving the electromechanical loads (relays, solenoids, dc motors, etc.) and incandescent lamps is described. The interface hardware is based on the Commodore VIC-20 microcomputer. The design is adaptable to most 8-bit microcomputers.     

Establishing normative data for repeated cognitive assessment: A comparison of different statistical methods

Serial cognitive assessment is conducted to monitor changes in the cognitive abilities of patients over time. At present, mainly the regression-based change and the ANCOVA approaches are used to establish normative data for serial cognitive assessment. These methods are straightforward, but they have some severe drawbacks. For example, they can only consider the data of two measurement occasions. In this article, we propose three alternative normative methods that are not hampered by these problems—that is, multivariate regression, the standard linear mixed model (LMM), and the linear mixed model combined with multiple imputation (LMM with MI) approaches. The multivariate regression method is primarily useful when a small number of repeated measurements are taken at fixed time points. When the data are more unbalanced, the standard LMM and the LMM with MI methods are more appropriate because they allow for a more adequate modeling of the covariance structure. The standard LMM has the advantage that it is easier to conduct and that it does not require a Monte Carlo component. The LMM with MI, on the other hand, has the advantage that it can flexibly deal with missing responses and missing covariate values at the same time. The different normative methods are illustrated on the basis of the data of a large longitudinal study in which a cognitive test (the Stroop Color Word Test) was administered at four measurement occasions (i.e., at baseline and 3, 6, and 12 years later). The results are discussed and suggestions for future research are provided.