Book contents
- Frontmatter
- Contents
- Foreword
- Preface
- 1 Epidemiology is…
- 2 How long is a piece of string? Measuring disease frequency
- 3 Who, what, where and when? Descriptive epidemiology
- 4 Healthy research: study designs for public health
- 5 Why? Linking exposure and disease
- 6 Heads or tails: the role of chance
- 7 All that glitters is not gold: the problem of error
- 8 Muddied waters: the challenge of confounding
- 9 Reading between the lines: reading and writing epidemiological papers
- 10 Who sank the boat? Association and causation
- 11 Assembling the building blocks: reviews and their uses
- 12 Outbreaks, epidemics and clusters
- 13 Watching not waiting: surveillance and epidemiological intelligence
- 14 Prevention: better than cure?
- 15 Early detection: what benefits at what cost?
- 16 A final word…
- Answers to questions
- Appendix 1 Direct standardisation
- Appendix 2 Standard populations
- Appendix 3 Calculating cumulative incidence and lifetime risk from routine data
- Appendix 4 Indirect standardisation
- Appendix 5 Calculating life expectancy from a life table
- Appendix 6 The Mantel-Haenszel method for calculating pooled odds ratios
- Appendix 7 Formulae for calculating confidence intervals for common epidemiological measures
- Glossary
- Index
- References
Appendix 6 - The Mantel-Haenszel method for calculating pooled odds ratios
- Frontmatter
- Contents
- Foreword
- Preface
- 1 Epidemiology is…
- 2 How long is a piece of string? Measuring disease frequency
- 3 Who, what, where and when? Descriptive epidemiology
- 4 Healthy research: study designs for public health
- 5 Why? Linking exposure and disease
- 6 Heads or tails: the role of chance
- 7 All that glitters is not gold: the problem of error
- 8 Muddied waters: the challenge of confounding
- 9 Reading between the lines: reading and writing epidemiological papers
- 10 Who sank the boat? Association and causation
- 11 Assembling the building blocks: reviews and their uses
- 12 Outbreaks, epidemics and clusters
- 13 Watching not waiting: surveillance and epidemiological intelligence
- 14 Prevention: better than cure?
- 15 Early detection: what benefits at what cost?
- 16 A final word…
- Answers to questions
- Appendix 1 Direct standardisation
- Appendix 2 Standard populations
- Appendix 3 Calculating cumulative incidence and lifetime risk from routine data
- Appendix 4 Indirect standardisation
- Appendix 5 Calculating life expectancy from a life table
- Appendix 6 The Mantel-Haenszel method for calculating pooled odds ratios
- Appendix 7 Formulae for calculating confidence intervals for common epidemiological measures
- Glossary
- Index
- References
Summary
When you do a stratified analysis to control for confounding you end up with a number of different odds ratios – one for each stratum. If these are all fairly similar, the next stage is to combine them into a single adjusted odds ratio that summarises the effect of the exposure adjusted for the confounder. Note that it is practical to do this only when you have a fairly small number of strata; once you need to adjust for more than one or two confounders it is better to use multivariable modelling techniques.
An adjusted odds ratio is essentially a weighted average of the stratum specific odds ratios. We calculate a weighted average rather than a straight average so that strata with more people (and therefore greater precision) have a bigger influence on the final result than small strata. To calculate a weighted average, each individual value is multiplied by its weight and these new values are then added up and divided by the sum of the weights. Various sets of weights can be used for pooling odds ratios, but those proposed by Mantel and Haenszel (1959) are commonly used.
- Type
- Chapter
- Information
- Essential EpidemiologyAn Introduction for Students and Health Professionals, pp. 413 - 415Publisher: Cambridge University PressPrint publication year: 2010