Get Statistical Methods in Medical Research, Fourth Edition PDF

By P. Armitage, G. Berry, J.N.S. Matthews(auth.)

ISBN-10: 0470773669

ISBN-13: 9780470773666

ISBN-10: 0632052570

ISBN-13: 9780632052578

The reason and implementation of statistical tools for the scientific researcher or statistician continues to be an essential component of recent clinical examine. This e-book explains using experimental and analytical biostatistics structures. Its obtainable type permits it for use through the non-mathematician as a primary section of profitable research.

Since the 3rd variation, there were many advancements in statistical suggestions. The fourth variation offers the scientific statistician with an obtainable advisor to those innovations and to mirror the level in their utilization in scientific research.

The new version takes a way more accomplished method of its topic. there was a thorough reorganization of the textual content to enhance the continuity and solidarity of the presentation and to increase the scope by way of overlaying many new rules now being brought into the research of clinical examine information. The authors have attempted to take care of the modest point of mathematical exposition that characterised the sooner variations, basically confining the maths to the assertion of algebraic formulae instead of pursuing mathematical proofs.

Received the hugely counseled certificates within the Public well-being type of the 2002 BMA Books Competition.Content:
Chapter 1 The Scope of information (pages 1–7):
Chapter 2 Describing facts (pages 8–46):
Chapter three likelihood (pages 47–82):
Chapter four Analysing capacity and Proportions (pages 83–146):
Chapter five Analysing Variances, Counts and different Measures (pages 147–164):
Chapter 6 Bayesian equipment (pages 165–186):
Chapter 7 Regression and Correlation (pages 187–207):
Chapter eight comparability of numerous teams (pages 208–235):
Chapter nine Experimental layout (pages 236–271):
Chapter 10 Analysing Non?Normal facts (pages 272–311):
Chapter eleven Modelling non-stop info (pages 312–377):
Chapter 12 extra Regression types for a continuing reaction (pages 378–454):
Chapter thirteen Multivariate tools (pages 455–484):
Chapter 14 Modelling specific info (pages 485–502):
Chapter 15 Empirical equipment for specific information (pages 503–527):
Chapter sixteen additional Bayesian equipment (pages 528–567):
Chapter 17 Survival research (pages 568–590):
Chapter 18 medical Trials (pages 591–647):
Chapter 19 Statistical equipment in Epidemiology (pages 648–716):
Chapter 20 Laboratory Assays (pages 717–741):

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Additional info for Statistical Methods in Medical Research, Fourth Edition

Example text

126). The essential point about logs is that, when numbers are multiplied together, their logs are added. If a series of numbers increases by a constant multiplying factor, their logs must increase by a constant difference. This is shown by the following series of values of a variable x, and the corresponding values of y ˆ log x. x y 2 0Á3 20 1Á3 200 2Á3 2000 3Á3 These four values of x are highly skew, with increasing differences between the higher values, whereas the values of y are symmetrically distributed, with equal differences between adjacent values.

4 that for skewly distributed variables, such as the duration of absence of work used as an illustration on p. 32, the mean may be a less satisfactory measure of location than the median. More generally, many of the methods of analysis to be described later in this book are more appropriate for 34 Describing data variables following an approximately symmetric distribution than for those with skew distributions. A useful device in such situations is the logarithmic (or log) transformation (or transform).

Thus, if such high counts were needed only to the nearest 10 units, they could be displayed as: 1** 199 2 5 representing 110, 190, 190 and 250. For other variants on stem-and-leaf displays, see Tukey (1977). If the main purpose of a visual display is to compare two or more distributions, the histogram is a clumsy tool. Superimposed histograms are usually confusing, and spatially separated histograms are often too distant to provide a means of comparison. The dot diagram of Fig. 5 or the box-and-whisker plot of Fig.

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Statistical Methods in Medical Research, Fourth Edition by P. Armitage, G. Berry, J.N.S. Matthews(auth.)

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