A BASIC program for randomizing and balancing the order of interventions in crossover studies.

F Salnitro; C Zoccali

doi:10.1016/0169-2607(89)90170-3

Home/Archive/PubMed

PubMed · 2924557

A BASIC program for randomizing and balancing the order of interventions in crossover studies.

F Salnitro·C Zoccali

View original source ↗Export metadata ↓

Abstract

The source did not provide an abstract. Follow the original record for more information.

Explore related subjects

Mathematical Computing Microcomputers Programming Languages Random Allocation Research Design Therapy, Computer-Assisted Journal Article

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

F Salnitro, C Zoccali. 1989. A BASIC program for randomizing and balancing the order of interventions in crossover studies.. https://doi.org/10.1016/0169-2607(89)90170-3

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed1992

On the suitability of semiempirical calculations as sources of force field parameters.

The suitability of Dewar's Hamiltonians as a source of bonded force field parameters is explored from the comparison analysis between up to 270 semiempirically derived force field parameters and experimentally derived values reported in some of the most popular force fields. From the statistical analysis of the results, some general conclusions about the semiempirical parametrization are formulated.

Mathematical Computing↗

PubMed1991

[Evaluation of non-occurrence by TI-59 programmable calculator].

A TI-59 programmable calculator program is presented for calculating either risk probability, sample size or confidence level (given 2 of the 3 variables) in cases in which an event of concern did not occur, or as expressed mathematically, had zero numerators. Its main usefulness is as a tool for interpreting previously published data containing no adverse event of concern while contemplating medical alternatives. These conditions are not infrequent in rare medical events--either diseases or complications. However, applicability of the program extends beyond these confines, exemplified in experimental planning for considering expected sample size or in calculating certainty in terms of confidence level.

Mathematical Computing↗

PubMed1991

Multivariate probit analysis: a neglected procedure in medical statistics.

The multivariate probit model is designed to regress a vector of correlated quantal variables on a mixture of continuous and discrete predictors. Various applications can be found in the biological, economical and psychosociological literature, but the method is not yet widely used in medical applications. We reintroduce this model thereby showing its usefulness in medical problems. Software for this model is, however, not widely available. We have written a PC program to select predictors and estimate parameters in the multivariate probit framework. The performance and characteristics of the program are briefly illustrated.

Mathematical Computing↗