Table Of ContentApplied Statistics
A HANDBOOK OF BMDP8 ANALYSES
E. J. SNELL
Department of Mathematics
Imperial College
London
A complement to
Applied Statistics
PRINCIPLES AND EXAMPLES
D. R. COX AND E. J. SNELL
Department i5f Mathematics
Imperial College
London
SPRINGER-SCIENCE+BUSINESS MEDIA, B.V.
© 1987 E.J. Snell
Originally published by Chapman and Hall in 1987
ISBN 978-0-412-28410-6
All rights reserved. No part of this book may be
reprinted, or reproduced or utilized in any form or by
any electronic, mechanical or other means, now known
or hereafter invented, including photocopying and
recording, or in any information storage and retrieval
system, without permission in writing from the
publisher.
British Library Cataloguing in Publication Data
Snell, F..J.
Applied statistics: a handbook of BMDP
analyses
1. BMDP (Computer program)
I. Title II. Cox, D.R. Applied statistics
519.5'028'55329 QA276.4
ISBN 978-0-412-28410-6 ISBN 978-94-011-6946-2 (eBook)
DOI 10.1007/978-94-011-6946-2
Library of Congress Cataloging in Publication Data
Snell, E. J.
Applied statistics.
"A complement to Applied statistics: principles and
examples [by] D.R. Cox and E.J. Snell."
Bibliography: p.
Includes index.
1. Mathematical statistics. 2. Medical statistics
Data processing. I. Cox, D. R. (David Roxbee). Applied
statistics. II. Title.
QA276.C6653 1981 Suppl. 519.5 86-21529
ISBN 978-0-412-28410-6
Contents
Foreword page vu
Preface IX
INTRODUCTION 3
BMDP programs used (or suggested) for the examples 5
Some points on the BMDP instructions 7
EXAMPLES 11
A Admissions to intensive care unit 13
B Intervals between adjacent births 18
C Statistical aspects of literary style 22
D Temperature distribution in a chemical reactor 26
E A 'before and after' study of blood pressure 31
F Comparison of industrial processes in the presence of trend 34
G Cost of construction of nuclear power plants 38
H Effect of process and purity index on fault occurrence 50
I Growth of bones from chick embryos 56
J Factorial experiment on cycles to failure of worsted yarn 61
K Factorial experiment on diets for chickens 67
L Binary preference data for detergent use 72
M Fertilizer experiment on growth of cauliflowers 78
N Subjective preference data on soap pads 85
0 Atomic weight of iodine 94
P Multifactor experiment on a nutritive medium 98
Q Strength of cotton yarn 104
R Biochemical experiment on the blood of mice 111
S Voltage regulator performance 115
T Intervals between the failure of air-conditioning equipment
in aircraft 121
U Survival times of leukemia patients 127
v
VI Contents
V A retrospective study with binary data 132
W Housing and associated factors 136
X Educational plans of Wisconsin schoolboys 142
FURTHER SETS OF DATA 151
Set 3 Survival times of rats 153
Set 14 Grouping of perfumes 162
References 167
Index 169
Foreword
This handbook is a realization of a long term goal of BMDP Statistical
Software. As the software supporting statistical analysis has grown in breadth
and depth to the point where it can serve many of the needs of accomplished
statisticians it can also serve as an essential support to those needing to expand
their knowledge of statistical applications. Statisticians should not be
handicapped by heavy computation or by the lack of needed options.
When Applied Statistics, Principle and Examples by Cox and Snell appeared
we at BMDP were impressed with the scope of the applications discussed and
felt that many statisticians eager to expand their capabilities in handling such
problems could profit from having the solutions carried further, to get them
started and guided to a more advanced level in problem solving. Who would
be better to undertake that task than the authors of Applied Statistics?
A year or two later discussions with David Cox and Joyce Snell at Imperial
College indicated that a wedding of the problem statements and suggested
solutions with control language to accomplish these analyses would further
the learning process for many statisticians. They were willing to undertake the
project.
Joyce Snell has done an excellent job of melding the two approaches and has
carried many of the problems a step further by suggesting alternate
approaches and follow-up analyses.
W. J. Dixon
BMDP Statistical Software
vii
Preface
Examples covering a wide range of statistical techniques are discussed in
Applied Statistics. Principles and Examples (Cox and Snell, 1981). Attention
there concentrates, not so much on computational details, but more on
general methodological issues and the interpretation of conclusions. It is
therefore recommended that students should work through the detailed
analyses themselves, to obtain the results discussed and examine the
conclusions from alternative or more extensive analyses. Even though some of
the sets of data are small enough for hand analysis, a computer can be helpful,
particularly when a complex or repetitive analysis is required.
The BMDP computer programs provide methods ranging from simple
plots and descriptive measures to the fitting of complex models. The present
handbook lists instructions for using BMDP programs to analyse all the
examples discussed in the previous book. The programs are shown to be useful
for both non-standard and standard statistical problems.
I am greatly indebted to Dr. W. J. Dixon for suggesting the preparation of
this handbook and for providing a Statcat microcomputer with BMDP
statistical software which made the task possible. I am most grateful also to
Linda Muthen, MaryAnn Hill and Jennifer Row of BMDP for their
invaluable help and guidance throughout the project and for preparing
camera-ready laser copies of the input and output. Finally I express my
appreciation to Sir David Cox for many helpful suggestions and for my earlier
pleasure in being a joint author with him of Applied Statistics. Principles and
Examples, which provides the basis for this handbook.
E. J. Snell
London, May 1986
ix
INTRODUCTION
Introduction
Instructions are given to enable the student to use BMDP statistical computer
programs to analyse the examples discussed in Applied Statistics. Principles
and Examples (Cox and Snell, 1981), hereafter referred to simply as App. Stat.
The aim throughout this handbook has been, as far as possible, to keep the
BMDP instructions simple yet to use the flexibility of the BMDP programs to
provide useful output and in particular to be able to reproduce the tables and
results discussed in App. Stat. The examples are labelled Example A, ... , X as
in that book and tables of results, etc., given there are referred to, for example,
as Table A.2, App. Stat.
Each set of data is reproduced in full, with a description of the data, exactly
as in App. Stat. in order to make this handbook, to some extent, self-contained
although it must be used in parallel with App. Stat. if full benefit from an
analysis is to be gained. Not all tables of results are reproduced here. Selected
items from the BMDP output (labelled Output A.1, ...) are shown and are
sufficient for the student to see that the relevant tables or results can be
obtained.
BMDP instructions are given for each Example A, ... , X and also for two
further data sets (Sets 3, 14; App. Stat.), the latter being selected as illustrating
the application of two BMDP programs for techniques not used in the main
examples. Notes are given beside the instructions as a help to students.
The statistical analyses range from very simple, barely justifying the use of a
computer, to complex, but for the sake of completeness each Example
A, .. . , X has been included. Example E is particularly simple, requiring only
plots but, as such, provides an easy starting point for anyone wishing for an
introduction to the use of BMDP programs. Likewise Example D, although
containing interesting discussion in App. Stat., here computes only a simple
regression and plots residuals. Example P involves straightforward multiple
regression. Other more complex problems involve the fitting oflogistic models
(Examples H, X), log-linear models (Example W), survival analysis (Set 3),
cluster analysis (Set 14) and specific models fitted by maximum likelihood
(Examples T, U). Example C provides a nonstandard analysis.
In a course of instruction, the order in which the examples should be taken
3
4 Introduction
will depend partly on the need to run simple programs first and partly on the
order in which statistical topics are discussed. Readers interested in using
BMDP for particular statistical applications, e.g. multiple regression, may go
straight to the relevant examples.
Sometimes more than one BMDP program is suitable for a particular
example, with one perhaps preferred for some aspects of the analysis. In such
cases either instructions are given for the alternative program or it is simply
presumed that a similar application in a different example will provide
sufficient guidance. A reference list of the BMD P programs used (or suggested)
for each example is given in the following section.
The BMDP instructions listed here have not been written by an expert in
statistical computing or by someone with long experience ofBMDP. The aim
has been to keep things at a simple level and to obtain the numerical results
quoted in App. Stat. in a way that a new user will find straightforward, natural
and appealing. Sometimes other analyses are also suggested. Reference to the
BMDP manual (Dixon et al., 1985) and user's digest (Hill, 1984) will
undoubtedly prove valuable. Some general points on the BMDP instructions
as used in the examples are given in the subsequent section.
The programs given in this handbook have been run using the 1985 release
of BMDP Statistical Software.
BMDP programs used
(or suggested) for the examples
Example BMDP programs Example BMDP programs
A 2D N 9D, 4F, 2V, (4V, 8V)
B lD, 6D 0 2V
c lD p 1R,9R
D lR, (2R) Q 7D, 8V, (3V)
E 6D R 8V, (2V)
s
F lR, (2R) 2V
G lR, 2R, 9R T AR, (3R)
u
H 3R, LR, (AR) 3R, (AR)
v
I lR, (2R) LR
J 9D, lR, (2R) w 4F
K 4V, (9D, 2V, 8V, lR, 2R) X 4F, LR
L 4V, LR, (2V, 1R, 2R) Set 3 1L,2L
M 1R, 2R, LR Set 14 1M, (4M)
(Instructions are not given for programs shown in brackets.)
Program descriptions
1D Simple data description
2D Detailed data description, including frequencies
6D Bivariate (scatter) plots
7D Description of groups (strata) with histograms and analysis of variance
9D Multiway description of groups
4F Two-way and multiway frequency tables-measures of association and
the log-linear model (complete and incomplete tables)
lL Life tables and survival functions
2L Survival analysis with covariates - Cox models
1M Cluster analysis of variables
5
