摘要:

Because missing observations may affect the size and power of statistical tests of equality, various analytical techniques explicitly or implicitly condition the analysis on the amount of information available per person. We illustrate the difference between stratifying a slope estimate and stratifying a test statistic based on slopes. We compare a nonparametric version of the latter approach with the parametric tests available from SAS Proc Mixed. Power and size of these two approaches are considered under different parametric settings, distributions, and missing data mechanisms.

ISSN:1054-3406    

DOI:10.1081/BIP-100101977

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

The notion of zero interaction in the statistical literature is not always equivalent to what is found in the toxicology literature. A discussion about when they are the same is provided here. Design issues are of paramount importance in the analysis of drug combinations (mixtures of chemicals) when the number of constituents in the combination is larger than, say, three as the usual factorial designs are not feasible. An economical design necessary and sufficient to support the estimation of an additivity model is single drug (chemical) dose-response data. Once estimated, the additivity surface can be used to make comparisons to the observed data at combination points of interest. Examples are provided to demonstrate the methods.

ISSN:1054-3406    

DOI:10.1081/BIP-100101978

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

ISSN:1054-3406    

DOI:10.1081/BIP-100101979

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

The U.S. Food and Drug Administration (FDA) is in the process of preparing a draft Guidance for Industry document on the statistical aspects of carcinogenicity studies of pharmaceuticals for public comment. The purpose of the document is to provide statistical guidance for the design of carcinogenicity experiments, methods of statistical analysis of study data, interpretation of study results, presentation of data and results in reports, and submission of electronic study data. This article covers the genesis of the guidance document and some statistical methods in study design, data analysis, and interpretation of results included in the draft FDA guidance document.

ISSN:1054-3406    

DOI:10.1081/BIP-100101980

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

The widely used distinction of Little and Rubin [1] about types of randomness for missing data presents difficulties in its application to dropouts in longitudinal repeated measurement studies. In its place, a new typology of randomness for dropouts is proposed that relies on using a survival model for the dropout process.

ISSN:1054-3406    

DOI:10.1081/BIP-100101981

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

The U.S. Food and Drug Administration (FDA) requires pharmaceutical companies to show bioequivalence between different formulations or generic companies to show bioequivalence between generic drugs and brand drugs before a9680186roval. In a recent FDA guidance on bioequivalence, new criteria were proposed for assessment of population and individual bioequivalence. In this article, computer simulation is used to compare a modified large sample (MLS) upper bound for the population bioequivalence ratio with the bootstrap upper bound recommended by the FDA. The comparison criteria are the ability to maintain the stated confidence level and the estimated power of tests based on these bounds.

ISSN:1054-3406    

DOI:10.1081/BIP-100101982

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

With immunoassay or bioassay data, the assay standards often exhibit considerable inter-assay variability. However, the assay controls, which are used to monitor the assay performance and set acceptance criteria, should have no or less interassay variability. In this paper, we develop a mixed-effect calibration model for the assay controls to set new acceptance criteria and qualify the enzyme-linked immunosorbent assay (ELISA) data, which incorporates the interassay variation of assay standards and the nature of the assay controls, and overcomes the problems caused by traditional fixed-effect calibration model.

ISSN:1054-3406    

DOI:10.1081/BIP-100101983

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

Patients for large-scale clinical trials are typically recruited from multiple centers to ensure adequate patient population and timely enrollment. In this note, carryover, treatment, and period effects for continuous data in multicenter studies with a 2 × 2 crossover design are examined using two types of covariate analysis adjusted for center effect proposed by Castellana and Patel [1]. The correspondence amongF-tests for various sources of variation in the two approaches is derived in detail. An example from a clinical study with complete and incomplete data is given to illustrate the use of the two types of covariate analysis. Also, the impact of complete and incomplete data on the covariate analyses is discussed along with the weighted squares of means analysis used in SAS procedure PROC GLM and residual maximum likelihood (REML) estimation employed in SAS procedure PROC MIXED.

ISSN:1054-3406    

DOI:10.1081/BIP-100101984

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

ISSN:1054-3406    

DOI:10.1081/BIP-100101985

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor