Statistical analysis of active extension trial / 中国临床药理学与治疗学

AIM: To estimate the treatment effect before and after patients stopped taking the drug, based on the combination of withdrawal randomized study and active extension trial design. METHODS: The short term treatment effect was estimated separately by the traditional method of using first stage data and the method of taking second or third stage data into consideration. And the treatment difference between long term and short term, also the treatment difference after patients discontinued from treatment were further assessed. The robustness of the result was tested by simulation assumed different scenario. RESULTS: The standard error (0.17) of the treatment effect estimation used more stage data was less than that of only used the first stage (Standard error: 0.19), besides much powerful for those treatment effect could be stabilized in the short period. CONCLUSION: Compared with the method only utilized the data of the first stage, the method developed here utilized second or third stage data. The utilization of more information leaded to decreasing of standard deviation and increasing of validity for the estimation of treatment effect. But the results will be influenced by the time required for the stabilization of the treatment effect, since the method was based on certain assumptions.

Ronda clínica y epidemiológica. Análisis de datos longitudinales / Clinical and epidemiological round. Longitudinal data analysis / Ronda clínica e epidemiológica. Análise de dados longitudinais

El denominado análisis de datos longitudinales (ADL) se refiere a los métodos para evaluar de manera apropiada las medidas de un mismo sujeto que se repiten en el tiempo. El ADL es una herramienta adecuada para entender indicadores de cambio en procesos de salud y enfermedad y para la evaluación del efecto de diversas intervenciones terapéuticas. Se presentan los principales modelos de ADL, sus ventajas y algunos ejemplos recientes de la literatura médica.

Longitudinal data analysis (LDA) refers to the methods designed to evaluate repeated measurements within an individual. LDA is an appropriate tool to address the process of change in health and disease and also to evaluate the efficacy of interventions. We present the main LDA models as well as their advantages and some clinical examples from recent medical literature.

A denominada análise de dados longitudinais (ADL) refere-se aos métodos para avaliar de maneira apropriada as medidas de um mesmo sujeito que se repetem no tempo. O ADL é uma ferramenta adequada para entender indicadores de mudança em processos de saúde e doença e para a avaliação do efeito de diversas intervenções terapêuticas. Apresentam-se os principais modelos de ADL, suas vantagens e alguns exemplos recentes da literatura médica.

What repeated measures analysis of variances really tells us / 대한마취과학회지

This article examined repeated measures analysis of variance (RMANOVA). Within-subjects repeated measurements are unavoidable during clinical and experimental investigation, and between- and within-subject variability should be treated separately. Only through proper use and meticulous interpretation can ethical and scientific integrity be guaranteed. The philosophical background of, and knowledge pertaining to, RMANOVA are described in the first half of this text. The sphericity assumption and associated issues are discussed in the latter half. The final section provides a summary measure analysis, which was neglected by P value-dependent interpreters.

Mixed linear model and its application to repeated measurements in single-sample / 第三军医大学学报

Objective To explore analysis method of repeated measurements in single-sample. Methods Mixed linear model was presented and an example of repeated measurements in single-sample was analyzed. Results The reasonable results were obtained for repeated measurements in single-sample by the methods of mixed linear model. Conclusion Mixed linear model can be used to analyze repeated measurement data in single-sample.

The Analysis of Repeated Measurements in a Long-term Treatment with a Kampo Prescription / 日本東洋医学雑誌

For the evaluation of the efficacy in a long-term treatment with a Kampo prescription, it is important to analyze repeated measurements based on their time course patterns.<br>In this paper, we analyze from the point of model selection with AIC the repeated measurements of platelet obtained from 24 Idiopathic Thrombocytopenic Purpura patients treated with a Kampo prescription (Sho-saiko-to) for 1 year. With the results, we analyze the repeated measurements obtained from another 6 patients of the same disease.