Biomaterial Database

Sample size and power for prospective analysis of relative risk. 1993

W C Blackwelder

National Institute of Allergy and Infectious Diseases, Bethesda, Maryland 20892.

In a placebo-controlled vaccine efficacy trial or a trial of equivalence of vaccines, one may wish to show that relative risk of disease is less than a specified value R0, not equal to one. This paper compares three methods for estimating relative risk in the binomial setting, based on a logarithmic transformation, likelihood scores, and a Poisson approximation. Exact power and size of test are calculated by enumeration of possible binomial outcomes, and power is approximated from asymptotic formulations. Although the score method is generally preferable, for most studies of practical interest the log and score methods are comparable, and the Poisson method is also appropriate for small risks, up to about 0.05. When true and null relative risks are less than one, unequal allocation of study individuals can increase power, and the asymptotic formula for the log method may substantially underestimate power; in such a study the power approximation for the score method is more reliable, even if the log method is used in analysis. Exact power calculations are helpful in planning studies. The log and Poisson methods, but not the score method, apply readily in the case of unequal follow-up.

UI	MeSH Term	Description	Entries
D010567	Pertussis Vaccine	A suspension of killed Bordetella pertussis organisms, used for immunization against pertussis (WHOOPING COUGH). It is generally used in a mixture with diphtheria and tetanus toxoids (DTP). There is an acellular pertussis vaccine prepared from the purified antigenic components of Bordetella pertussis, which causes fewer adverse reactions than whole-cell vaccine and, like the whole-cell vaccine, is generally used in a mixture with diphtheria and tetanus toxoids. (From Dorland, 28th ed)	Vaccine, Pertussis
D005500	Follow-Up Studies	Studies in which individuals or populations are followed to assess the outcome of exposures, procedures, or effects of a characteristic, e.g., occurrence of disease.	Followup Studies,Follow Up Studies,Follow-Up Study,Followup Study,Studies, Follow-Up,Studies, Followup,Study, Follow-Up,Study, Followup
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D012306	Risk	The probability that an event will occur. It encompasses a variety of measures of the probability of a generally unfavorable outcome.	Relative Risk,Relative Risks,Risk, Relative,Risks,Risks, Relative
D012494	Sampling Studies	Studies in which a number of subjects are selected from all subjects in a defined population. Conclusions based on sample results may be attributed only to the population sampled.	Probability Sample,Probability Samples,Sample, Probability,Samples, Probability,Sampling Study,Studies, Sampling,Study, Sampling
D014611	Vaccination	Administration of vaccines to stimulate the host's immune response. This includes any preparation intended for active immunological prophylaxis.	Immunization, Active,Active Immunization,Active Immunizations,Immunizations, Active,Vaccinations
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D016010	Binomial Distribution	The probability distribution associated with two mutually exclusive outcomes; used to model cumulative incidence rates and prevalence rates. The Bernoulli distribution is a special case of binomial distribution.	Bernoulli Distribution,Negative Binomial Distribution,Binomial Distribution, Negative,Binomial Distributions,Binomial Distributions, Negative,Distribution, Bernoulli,Distribution, Binomial,Distribution, Negative Binomial,Distributions, Binomial,Distributions, Negative Binomial,Negative Binomial Distributions