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Biomedical subjects

H Robbins

Publications and source records attributed to H Robbins.

At least 55 records · Page 3Linked to original sources
PubMed1974

A sequential test for two binomial populations.

A sequential procedure is proposed for deciding which of two sequences of Bernoulli trials has the greater success probability. The procedure covers cases in which the two sequences are being observed at different rates, whether by design or otherwise, as well as the case of pairwise observation. The error probability of the procedure depends approximately only on the odds ratio of the two probabilities, a desirable property in deciding which of two medical treatments has the greater probability of success.

Journal Article↗
PubMed1972

Reducing the number of inferior treatments in clinical trials.

In clinical trials comparing two treatments, one would often like to control the probability of erroneous decision while minimizing not the total sample size but the number of patients given the inferior treatment. To do this obviously requires that one use a datadependent allocation rule for the two treatments rather than the conventional equal sample size scheme, whether fixed or sequential. We show here how this may be done in the case of deciding which of two normally distributed treatment effects has the greater mean, when the variances are assumed to be equal and known. Similar methods can be used under other hypotheses on the underlying probability distributions, and will provide a considerable increase in flexibility in the design of sequential clinical trials.

Clinical Trials as Topic↗
PubMed1970

Group practice.

Explore the source record for details and available documents.

Group Practice, Dental↗
PubMed1969

Probability distributions related to the law of the iterated logarithm.

Let W(t) denote a standard Wiener process for 0 </= t < infinity. We compute the probability that W(t) >/= t((1/2))A(t) for some t >/= 1 (or for some t >/= 0) for a certain class of functions A(t), including functions which are approximately (2 log log t)((1/2)) as t --> infinity. We also give an invariance principle which states that this probability is the limit as m --> infinity of the probability that s(n) >/= n((1/2))A(n/m) for some n >/= m (or for some n >/= 1), where s(n) is the sum of n independent and identically distributed random variables with mean 0 and variance 1.

Journal Article↗