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Biomedical subjects

G A Seber

Publications and source records attributed to G A Seber.

12 recordsLinked to original sources
PubMed2001

Capture-recapture, epidemiology, and list mismatches: several lists.

In applying capture-recapture methods for closed populations to epidemiology, e.g., in the estimation of the size of a diabetes population, one comes up against the problem of list errors due to mistyping or misinformation. This problem has been studied for just two lists by Seber, Huakau, and Simmons (2000, Biometrics 56, 1227 1232) using the concept of tag loss borrowed from animal population studies. In this article, we discuss a similar method that can be extended to an arbitrary number of lists. The methods are applied to an example.

Animals↗
PubMed2000

Capture-recapture, epidemiology, and list mismatches: two lists.

In recent years, capture-recapture methods for closed populations have been extensively applied to epidemiology. For example, suppose we have several incomplete lists of diabetics and we wish to estimate the total number of diabetics by estimating the number missing from all the lists. A major problem is that the information about individuals on the lists may have been given incorrectly or the information may have been typed incorrectly so that some list matches are missed. Using the concept of tag loss borrowed from animal population studies, we consider methods for estimating both the probabilities of making list errors and the population size for just two independent lists. The effect of heterogeneity on the errors is examined. The methods are applied to a large data set of diabetic persons consisting of a list obtained from a survey and a list obtained from doctors' records. It was found that the error rates were high and that ignoring the errors led to a gross overestimate of the total number of diabetic persons.

Biometry↗
PubMed1994

Detectability in conventional and adaptive sampling.

In this paper a simple but very general method is given for estimating a population total with any sampling design when objects in sampled units are observed with imperfect detectability--a problem characteristic of many surveys of natural and human populations. In the most general case, the method consists of dividing the value of the variable of interest associated with each detected object by the detection probability for that object and then proceeding to use the estimation method that would ordinarily be used under the design if there were no detectability problems. Examples illustrating the method include simple random sampling, conventional unequal probability sampling, and adaptive cluster sampling.

Analysis of Variance↗
PubMed1992

Estimating blood phenotype probabilities and their products.

We consider two methods of estimating phenotype probabilities for a number of standard genetic markers like the ABO, MNSs, and PGM markers. The first method is based on the maximum likelihood estimates of the allele probabilities, and the second (multinomial) method uses the phenotype proportions in the sample. The latter is easy to use, the estimates are always unbiased, and simple formulae for variances are available. The former method, although giving more efficient estimates, requires the assumption of panmixia so that the Hardy-Weinberg law can be used. The two methods are compared theoretically, where possible, or by simulation. Under panmixia, the maximum likelihood estimates can be substantially more efficient than the multinomial estimates. The estimates are also compared in the codominant allele case for nonpanmictic populations. The question of efficiency is of importance when estimating the probability of obtaining a given set of phenotypes, i.e., the product of individual phenotype estimators. This problem is discussed briefly.

ABO Blood-Group System↗
PubMed1987

Paternity testing 3: exclusion probabilities.

Blood typing with several blood systems is used in many countries to determine paternity or nonpaternity with respect to an alleged father. Various probabilities are usually presented, in particular: the conditional probability of excluding a random man as father given a particular mother-child phenotype combination, and the expected (unconditional) exclusion probability for all mother-child combinations can be calculated for a given blood system. Because these probabilities are of general interest in paternity studies, explicit formulae for the unconditional probabilities have been derived for some of the systems. Algorithms suitable for a microcomputer are given here for finding the exclusion probabilities for any system. These algorithms avoid the need for developing new formulae whenever a new system is introduced or a current system is extended through the addition of further alleles.

Algorithms↗
PubMed1986

A review of estimating animal abundance.

During the past 5 years there have been a number of important developments in the estimation of animal abundance and related parameters such as survival rates. Many of the new techniques need to be more widely publicized as they supplant previous methods. The aim of this paper is to review this literature and suggest further avenues for research.

Animals↗
PubMed1985

Paternity testing. 2: Likelihood ratio tests.

It is known that the so-called paternity index is also a likelihood ratio statistic for testing that an alleged father is the true father. Unfortunately the likelihood ratio test can sometimes lead to unsatisfactory results because of its dependence on the phenotype combinations of the mother and child. A new, conditional likelihood ratio test, which we call the ancillary test, is proposed in which statistical testing is carried out conditionally on the phenotypes of the mother and alleged father. An exact procedure is available which can be executed with reasonable facility on a microcomputer.

Blood Group Antigens↗
PubMed1983

Paternity testing: I. Calculation of paternity indexes.

An algorithm, readily adaptable to microcomputers, is given for computing paternity indexes. A closed-form expression based only on gene frequencies and phenotype structures is derived for the paternity index for a given mother/child/alleged father trio and any blood group system. This above work is applied to the problem of estimating gene frequencies from sample data.

Blood Group Antigens↗
PubMedDate not supplied

Blood groups and other genetic markers in New Zealand Europeans and Maoris.

Genetic data on the frequency of various red-cell antigens and enzymes as well as polymorphic protein markers from New Zealand European and Maori populations are outlined. Despite widespread intermarriage between races in New Zealand there was, in nearly all systems tested, a significant difference in the frequency of genetic markers.

Blood Group Antigens↗