Power and sample size for health researchers: uma ferramenta para cálculo de tamanho amostral e poder do teste voltado a pesquisadores da área da saúde / Power and sample size for health researchers: a tool for calculating sample size and statistical power designed for health researchers

Nas próximas edições da seção de Bioestatística da revistaClinical & Biomedical Researchuma nova série de artigos será publicada abordando um assunto de grande importância ao planejar uma pesquisa: o tamanho de amostra mínimo necessário para atingir os objetivos do estudo. Nessa série será apresentado como calcular o tamanho de uma amostra usando a ferramenta PSSHealth(Power and Sample Size for Health Researchers), construído em linguagem R por meio do pacote Shiny, para diferentes tipos e objetivos de estudo, direcionado à pesquisadores da área da saúde, utilizando termos e conceitos comumente utilizados nesta área. Além disso, o pacote fornece uma sugestão de texto com as informações consideradas no cálculo, e como devem ser descritas, com a finalidade de minimizar problemas de interpretação por parte dos pesquisadores. Neste primeiro artigo será apresentada essa ferramenta desenvolvida pela Unidade de Bioestatística do Grupo de Pesquisa e Pós-Graduação do Hospital de Clínicas de Porto Alegre, que permite calcular não apenas o tamanho de amostra, mas também o poder de um teste de hipóteses. (AU)

In the next issues ofClinical and Biomedical Research, the Biostatistics section will introduce a new series of articles addressing a very important subject for research planning: the minimum sample size to achieve the aim of a study. This series will show how to calculate sample size using PSS Health (Power and Sample Size for Health Researchers). This tool was built using R language through the Shiny package. It can be used for different types of study and is designed for health researchers by using terms and concepts commonly used in this area. PSS Health also suggests a text with information considered in the calculation to minimize problems of interpretation by the researchers. In this first article, a general overview of PSS Health will be presented. This tool, which was developed by the Research and Graduate Group Biostatistics Unit of the Hospital de Clínicas de Porto Alegre, is useful not only to calculate sample size but also to determine power of a hypothesis test. (AU)

Study on the differences of Chinese handwriting characteristics among different population / 中华行为医学与脑科学杂志

Objective To investigate the differences of handwriting characteristics among different genders,educational backgrounds and ages. Methods The ESP1020 was used to collect 1 474 handwriting samples throughout the country,and the collected handwriting samples were quantized by the self-developed" HCAS" software. The system could automatically extract 36 objective handwriting features,such as the aver-age character area,at the same time,4 subjective handwriting features such as the overall beauty are quanti-fied by the " overall impression evaluation method" . Finally,forty handwriting characteristics data were intro-duced into SPSS23. 0 for statistical analysis. Results There were statistically significant differences in 11 handwriting characteristics between male and female,such as average Chinese characters height ((6. 960± 1. 843) mm,(6. 757±1. 762) mm,t=2. 16,P<0. 05). There were statistically significant differences in 21 handwriting characteristics between the groups with different educational backgrounds,including the average Chinese characters area in primary school and junior high school((52. 175 6± 33. 989 5) mm2 ),in senior high school and technical secondary school(( 64. 320 7 ± 63. 123 5) mm2 ) and in junior college or above ((63. 815 3±58. 147 4)mm2)(t=5. 42,P<0. 01). There were statistically significant differences in 28 hand-writing characteristics in different age groups,such as writing time,pen pressure and Chinese characters area (P<0. 05,P<0. 01). Conclusions Demographic variables such as gender,education background and age have different effects on different aspects of handwriting characteristics.

Introduction of Single Subject Designs as New Experimental Designs. (I). Their practical methods and comparison with group comparison designs / 全日本鍼灸学会雑誌

The present-paper introduced the logics and practical methods of single subject designs by comparing them with group comparison designs. It was pointed out that the single subject designs assert that controlling variables for a subject's behavior should be identified using individual analysis. Those characteristics were summarized as (a) acquisition of steady state data resulting from repeated measurement of target behaviors, and (b) identification of the functional relationship between experimental variables and dependent variables by successive comparison between baseline and experimental condition. The methods, advantages and problems in the principal single subject designs, such as AB design, reversal designs, multiple baseline design and alternating treatments design were explained. Several problems in the group comparison designs were pointed out and the possibilities for applying the single subject designs to research on acupuncture were discussed.