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  • SOME STATISTICAL ASPECTS

    OF

    THE GENERAUZABll..ITY OF OCCUPATIONAL HEAL Til STUDIES

  • Design cover: Pennarts Graphics Design, Hoiland

    Printed by: Casparie Heerhugowaard, Holland

  • SOME STATISTICAL ASPECTS

    OF

    THE GENERALIZABIUTY OF OCCUPATIONAL HEALTH STUDIES

    Statistische aspecten betreffende de generaliseerbaarheid

    van studies uitgevoerd binnen de bedrijfsgezondheidszorg

    PROEFSCHRIFT

    ter verkrijging van de graad van doctor

    aan de Erasmus Universiteit Rotterdam

    op gezag van de rector rnagnificus

    Prof. Dr C.J. Rijnvos

    en volgens besluit van het College van Dekanen.

    De openbare verdediging zal plaatsvinden op

    woensdag 22 januari 1992 om 13.45 uur

    door

    Dirk Lugtenburg

    geboren te Zuidland

  • PROMOTIE COMMISSIE

    Promotor: Prof. R. van Strik

    Overige !eden: Prof. Dr Ir. J.D.F. Habbema

    Prof. Dr J.J. Kolk

    Prof. Dr W. Molenaar

  • .... incompleteness may be due to the method of investigation itself such as the double

    sample procedures in large scale sample surveys. H the measurement of the character

    to be estimated is e>.-pensive, a small sample of individuals is chosen to supply

    measurements of this character together with a number of concomitant characters

    which are relatively inexpensive to measure. Then a large sample is taken for the

    concomitant characters only. The former sample provides the regression equation and

    the latter the estimates of mean values of the concomitant characters which are

    substituted in the regression equation to obtain the estimates for the main character

    under study.

    C. R. Rao (1956)

    Aan mijn ouders

  • CONTENTS

    Chapter I

    Chapter 2

    Chapter 3

    Chapter4

    Chapter 5

    Chapter 6

    Chapter 7

    Chapter 8

    Chapter 9

    Chapter 10

    Introduction

    Missing-data-generating mechanisms and their effects on

    the selection of methods of statistical analysis: a review

    The effects of loss-to-follow-up on estimates of relative risk

    Modelling manipulated discrete processes: estimating

    prevalence in the case of non-response

    An approximate Bartlett adjustment for testing the

    goodness of fit of multinomial regression models

    Small-sample results obtained with the unconditional

    Wilcoxon-Mann-Whitney test statistic for ordinal data

    Participants and non-participants in a trial of a back school

    education programme

    A statistical method for evaluating y-glutarnyltransferase in

    occupational health screening

    A general approach to the correction for bias in analytical

    performance in longitudinal studies: estimating the effect

    of age on y-glutamyltransferase

    General discussion

    Summary

    Samenvatting

    Dankwoord

    Curriculum vitae

    page

    9

    19

    35

    47

    61

    71

    85

    101

    115

    131

    137

    139

    141

    143

  • CHAPTERl

    INTRODUCTION

    11 ••• it is hardly an exaggeration to say that all studies

    published to date contain at least some systematic

    errors ........ n

    S. Hem berg (1986)

    9

  • 1.1 SOME STATISTICAL ASPECTS OF THE GENERALIZABILITY OF

    OCCUPATIONAL HEALTH STUDIES

    Occupational health departments screen employees during voluntary periodic health

    assessments for possible early indications of ill health. These assessments are based,

    among other things, on reference ranges for liver parameters, kidney parameters and

    other blood parameters. After a period of, say, ten years, data thus collected can also

    be used for large-scale epidemiologic studies. In such studies, long-term risk

    assessments may be made, either for early death or for specific diseases such as

    ischaemic heart disease. Conclusions drawn from these studies can have a direct

    influence on the short-term advice to specific employees on the basis of findings from

    periodic health assessments, as well as on the contents of these assessments. Factors

    such as exposure to chemicals, noise and physical exertion are being studied in these

    epidemiologic studies (Monson, 1980). Funhermore, known determinants of disease in

    general populations may be studied separately in occupational populations, in order to

    investigate whether these determinants are less important in such healthy cohorts.

    Apart from epidemiologic studies, well-designed trials are currently being introduced

    in occupational health environments, in order to assess the effects of interventions in

    life style habits of employees.

    Hartley and Hocking mentioned in 1971 that "the evil of incompleteness is

    most frequently encountered with data routinely collected .... such as .... based on

    surveys~~. Their remark, alas, is still valid. Incomplete records still constitute a major

    problem in studies based on data routinely collected at periodic health assessments.

    The quality of the available data is always debatable, too, and should be studied

    critically. Since in a large occupational health study, both problems are quite often

    encountered at the same time, they should be addressed by means of special

    methodology, e.g., through small studies on either incomplete observations or on the

    quality of data, the results of which can be used to adjust the conclusions from the

    large study for bias. Such a systematic approach of these problems of incomplete

    records and questionable quality of data enables generalizations from such large

    occupational health studies.

    With regard to the principles of reliability of a study it is useful to recall two

    relevant concepts: internal and external validity (Karvonen and Mikheev, 1986).

    Internal validity is achieved when no systematic errors are present within a study,

    whereas external validity goes beyond the population actually studied. Internal validity

    of a study comprises validity of selection, information and comparison. To ensure

    10

  • validity of selection, the probability of selection of individuals should not depend, in

    any way, on the parameter under study. This refers directly to the problem of missing

    data. Validity of information means that information gathered from all the subjects is

    similar, irrespective of the category to which they belong, which refers to the problem

    of quality of data. The validity of comparison has to do with correctly defining

    reference populations and is embedded in the previous two items. The present thesis

    discusses methods for assessing validity of selection and validity of information. To this

    end, it presents methods that may help to remove bias caused by either incomplete

    records or poor quality of data. Ex-trapolation of results or methods towards the area

    of ex'ternal validity is beyond the scope of this thesis.

    The problems of missing data and misclassification are also conceivable in

    small health studies. Here, however, they should be avoided by taking adequate

    measures at the design phase. If this is not done, any statistical significance observed

    might be due to npossibly erroneously collected data'\ which, certainly for large-scale

    studies, would not be acceptable as a way out. An additional problem with small

    studies is that asymptotic results cannot be used in an adequate description of the

    behaviour of test statistics. Generalizability can only be achieved if this behaviour is

    known, at least under the null hypothesis. This will be a separate topic in this thesis.

    1.2 THE SIMILARITY BETWEEN INCOMPLETENESS OF OBSERVATIONS

    AND DUBIOUS QUALITY OF DATA

    The most simple way of dealing with incomplete records is to remove them before

    calculating the statistics on which interest focusses. The conclusions, however, are then

    to be ristricted to the subsample of subjects of whom all data are (or can be) known.

    These strong restrictions can only be removed through the use of a strategy to deal

    with missing data. Three general approaches are found in the literature. Firstly, there

    is gaining actual information on the missing-data-generating process by resampling in

    the subsample of individuals with incomplete records, resulting in adjustment of

    conclusions derived from the sample of complete records. Secondly, postulating

    various missing-data-generating processes to be operative and studying their effects on

    important conclusions. Thirdly, imputing 'probable values' for missing data, and

    performing standard statistical analyses. In this thesis, a review of relevant recent

    literature will be presented, from which it will become clear that, if no extra

    information can be gathered by the first approach, a sensitivity analysis by the second

    11

  • approach may help to predict any dependence of relevant findings on assumptions

    concerning the missing-data-generating mechanism.

    In the area of misclassifica