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J R Landis

Publications and source records attributed to J R Landis.

11 recordsLinked to original sources
PubMed1979

A computer program for testing average partial association in three-way contingency tables (PARCAT).

PARCAT is a computer program which implements alternative tests for average partial association in three-way contingency tables within the framework of the product multiple hypergeometric probability model. Primary attention is directed at the relationship between two of the variables, controlling for the effects of a covariable. This approach is essentially a multivariate extension of the Cochran/Mantel-Haenszel test to sets of (s x r) tables. A set of scores such as uniform, ridits, or probits can be assigned to categories which are ordinally scaled. In particular, if ridit scores with midranks assigned for ties are utilized, this procedure is equivalent to a partial Kruskal-Wallis test when one variable is ordinally scaled, and is equivalent to a partial Spearman rank correlation test when both variables are ordinally scaled.

Age Factors↗
PubMed1978

Reliability of the Group for Advancement of Psychiatry Diagnostic Categories in Child Psychiatry.

A total of 403 multiple diagnoses were independently assigned to 41 patient protocols by 73 psychiatrists, psychologists, and social workers to determine the levels of interrater reliability of the Group for the Advancement of Psychiatry (GAP) diagnostic categories. With the exception of the psychotic disorders category, these diagnostic categories were found to have low levels of interdiagnostician reliability. Differences in the reliabilities across disciplines and levels of training were found. It is noted, however, that neither years of experience, kind of training, nor direct contact with the patient can be regarded as a substitute for improvements in the classification system itself. The importance of a reliable classification system for child psychiatry is emphasized and suggestions for improvements in the present GAP system are made.

Child↗
PubMed1978

A computer program for multivariate ratio analysis (MISCAT).

Analysts must deal frequently with missing data in multivariate analysis. In such cases, estimating the covariance maxtrix V of the dependent variables usually involves initial estimation and iterative adjustment of imputed missing data values, and/or smoothing of an estimate V which is not necessarily positive semi-definite. This paper presents an alternative procedure for computing estimates of relevant multivariate parameters in situations where missing data occur at random and with small probability. MISCAT is a computer program which computes multivariate ratio estimates of the means and a corresponding positive semi-definite estimate of the covariance matrix. It is an extension of GENCAT, which is a program for the generalizaed least squares analysis of categorical data. Thus, one advantage of dealing with missing data in this manner is that variation among the ratio estimates may be conveniently analyzed within MISCAT using asymptotic regression methodology, provided that sample sizes are sufficiently large. An example is given to illustrate such analysis for longitudinal data from a multicenter clinical trial.

Computers↗
PubMed1978

A computer program for the generalized chi-square analysis of competing risks grouped survival data (CRISCAT).

CRISCAT is a computer program for the analysis of grouped survival data with competing risks via weighted least squares methods. Competing risks adjustments are obtained from general matrix operations using many of the strategies employed in a previously developed program (GENCAT) for multivariate categorical data. CRISCAT computes survival rates at several time points for multiple causes of failure, where each rate is adjusted for other causes in the sense that failure due to thes other causes has been eliminated as a risk. The program can generate functions of the adjusted survival rates, to which asymptotic regression models may be fit. CRISCAT yields test statistics for hypotheses involving either these functions or estimated model parameters. Thus, this computational algorithm links competing risks theory to linear models methods for contingency table analysis and provides a unified approach to estimation and hypothesis testing of functions involving competing risks adjusted rates.

Actuarial Analysis↗
PubMed1977

Utilization and acceptability of influenza A/New Jersey/76 virus vaccine in Oakland County, Michigan.

The program of mass inoculation of adults in Oakland County, Michigan, with monovalent influenza A/New Jersey/76 virus vaccine was monitored. A stratified random sample of participants was selected, and telephone interviews were conducted two days after inoculation. The group of vaccines differed from the overall county population in that it had a higher percentage of females and more of the vaccinees were older, better educated, and of higher income. Minor complaints following vaccination were relatively frequent, particularly sore arm. All complaints were significantly more frequent in females than in males, and among females, the group younger than 40 years reported these complaints most often. Since neither utilization of the vaccine nor complaints following vaccination were uniformly distributed, it was concluded that population-based studies are needed for proper assessment of vaccine-related effects.

Adolescent↗
PubMed1977

A new technique for measuring preferences in demographic studies.

In this article, we introduce an alternative technique to the single-sentence question for measuring preferences for number of children, age at marriage, length of first birth interval, length of employment, and years of schooling. This new measurement procedure utilizes a graphic scale rather than verbal responses, and it places family size decisions within the context of several other major life cycle decisions. One month reliability data for the measurement technique were obtained from a sample of 107 school children. Reliability results are compared to data from a previous study of teenagers.

Adolescent↗
PubMed1977

A general methodology for the analysis of experiments with repeated measurement of categorical data.

This paper is concerned with the analysis of multivariate categorical data which are obtained from repeated measurement experiments. An expository discussion of pertinent hypotheses for such situations is given, and appropriate test statistics are developed through the application of weighted least squares methods. Special consideration is given to computational problems associated with the manipulation of large tables including the treatment of empty cells. Three applications of the methodology are provided.

Drug Evaluation↗
PubMed1977

The measurement of observer agreement for categorical data.

This paper presents a general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies. The procedure essentially involves the construction of functions of the observed proportions which are directed at the extent to which the observers agree among themselves and the construction of test statistics for hypotheses involving these functions. Tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interobserver agreement are developed as generalized kappa-type statistics. These procedures are illustrated with a clinical diagnosis example from the epidemiological literature.

Humans↗
PubMed1976

A computer program for the generalized chi-square analysis of categorical data using weighted least squares (GENCAT).

GENCAT is a computer program which implements an extremely general methodology for the analysis of multivariate categorical data. This approach essentially involves the construction of test statistics for hypotheses involving functions of the observed proportions which are directed at the relationships under investigation and the estimation of corresponding model parameters via weighted least squares computations. Any compounded function of the observed proportions which can be formulated as a sequence of the following transformations of the data vector--linear, logarithmic, exponential, or the addition of a vector of constants--can be analyzed within this general framework. This algorithm produces minimum modified chi-square statistics which are obtained by partitioning the sums of squares as in ANOVA. The input data can be either: (a) frequencies from a multidimentional contingency table; (b) a victor of functions with its estimated covariance matrix; and (c) raw data in the form of integer-valued variables associated with each subject. The input format is completely flexible for the data as well as for the matrices.

Biometry↗