A FORTRAN subroutine for sound production on the Amiga microcomputer

This article describes a FORTRAN 77 subroutine which manipulates the audio hardware facilities on the Amiga microcomputer. The subroutine may be instructed to produce either tones or musical notes on any combination of four independent channels. Frequency, volume, and type of waveform are passed to the subroutine as parameters. Some limitations in relation to sound production on the Amiga are discussed.     

Obtaining squared multiple correlations from a correlation matrix which may be singular

A theorem is presented relating the squared multiple correlation of each measure in a battery with the other measures to the unique generalized inverse of the correlation matrix. This theorem is independent of the rank of the correlation matrix and may be utilized for singular correlation matrices. A coefficient is presented which indicates whether the squared multiple correlation is unity or not. Note that not all measures necessarily have unit squared multiple correlations with the other measures when the correlation matrix is singular. Some suggestions for computations are given for simultaneous determination of squared multiple correlations for all measures.The research reported in this paper was supported by the Personnel and Training Branch of the Office of Naval Research under Contract Number 00014-67-A-0305-0003 with the University of Illinois.     

Matfit: A fortran subroutine for comparing two matrices in a subspace

This research was supported by grant APA 3020 from the Natural Sciences and Engineering Research Council of Canada. The author would like to thank Dr. David O'Hare for providing the data used to illustrate the use of the program MATFIT.     

SCORIT: A computer subroutine for scoring electrodermal responses

Given digitized electrodermal response records sampled at a rate of 20/sec and at a sensitivity level between 140 and 170 ohms, a computer subroutine for scoring skin resistance responses is described. It is designed to score multiple responses on a trial, which makes it particularly suitable for classical conditioning experiments involving long interstimulus intervals. The subroutine returns to the main program response latency, base resistance, peak resistance, and time from base to peak. Since SCORIT is written in FORTRAN IV, it can be employed in virtually any modern central computing facility at costs substantially below those involved in hand scoring.     

Allowing for correlations between correlations in random-effects meta-analysis of correlation matrices

Practical meta-analysis of correlation matrices generally ignores covariances (and hence correlations) between correlation estimates. The authors consider various methods for allowing for covariances, including generalized least squares, maximum marginal likelihood, and Bayesian approaches, illustrated using a 6-dimensional response in a series of psychological studies concerning prediction of exercise behavior change. Quantities of interest include the overall population mean correlation matrix, the contrast between the mean correlations, the predicted correlation matrix in a new study, and the conflict between the existing studies and a new correlation matrix. The authors conclude that accounting for correlations between correlations is unnecessary when interested in individual correlations but potentially important if concerned with a composite measure involving 2 or more correlations. A simulation study indicates the asymptotic normal assumption appears reasonable. Because of potential instability in the generalized least squares methods, they recommend a model-based approach, either the maximum marginal likelihood approach or a full Bayesian analysis.     

NORMUL: A FORTRAN program for testing multivariate normality

NORMUL is a FORTRAN program that provides a test of whether data conform to a multivariate normal distribution. The method involves correlating Mahalanobis distances for observed data with expected chi-square percentile values. This obtained correlation is then tested for significance by empirically evaluating the probability of its belonging to a distribution generated from multivariate normal data.     

A note on multiple and canonical correlation for a singular covariance matrix

A weaker generalized inverse (Rao's g-inverse; Graybill's c-inverse) can be used in place of the Moore-Penrose generalized inverse to obtain multiple and canonical correlations from singular covariance matrices.The author expresses his gratitude to a referee for his suggestions.