Presenting Medical Statistics from Proposal to Publication: A Step-by-step Guide
As many medical and healthcare researchers have a love-hate relationship with statistics, this practical reference book may make all the difference. It takes examples, mainly from the authors' own research, to explain how to make sense of statistics, turn statistical computer results into coherent information, and help decide which pieces of information to report and how to present them. Presenting Medical Statistics includes a wide range of statistical analyses, and all the statistical methods are illustrated using real data. Labelled figures show the Stata and SPSS commands needed to obtain the analyses, with indications of which information should be extracted from the output for reporting. The relevant results are then presented as for a report or journal article, to illustrate the principles of good presentation. The reader is taken through the various stages of the research process, from the initial research proposal, ethical approval and data analysis, to reporting on and publishing the findings. There are even extensive references for those who wish to find out more about the statistical methods. This is a must for anyone working with statistics in the medical profession.
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2 Introduction to the research process
3 Writing a research protocol
4 Writing up a research study
5 Introduction to presenting statistical analyses
6 Single group studies
7 Comparing two groups
8 Analysing matched or paired data
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adjusted Aim of analysis Aim of study Altman analysis of variance assumptions back-transformed bacterial vaginosis blood pressure caffeine case–control study Chapter chi-squared test cigs/day cluster coded compared Conf confidence interval CONSORT cotinine Cox regression described Description Methods section design Cohort study diabetes early pregnancy effect Epi-Info Error estimate example Presenting Figure geometric means gestational age give graph groups hazard ratio interquartile range intervention investigate Kaplan–Meier Kirkwood and Sterne log-transformed logistic regression Model multiple regression nausea Normal distribution number of subjects Obs Mean Std odds ratio overall P value patients pefr percentage population predictor variables Presenting the results prevalence proportions protocol recruitment reference category regression analysis regression coefficients relationship relative risk reported Results section risk factors sample size calculations scatterplot Select Analyze sensitivity and specificity shows significant skewed smoking standard deviation Stata and SPSS study Aim Study design Cohort summary statistics Total transformation UKOS wheeze women