Assumptions for Different Ascertainment Models in Human Genetics

Js, Williams; Stene, Jon

doi:10.2307/2529367

Cited by 33 publications

(13 citation statements)

References 3 publications

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“…These conclusions are evinced by the graphs in Figure 1. From this point of view, ascertainments with ε = -1 and -2 are expected to be more effective (their feasibility has already been considered by Stene [1977] and Ginsburg and Axenovich [1992]). Figure 1 confirms expectation that these strategies will be more effective.…”

Section: Results and Discussion Required Sample Sizementioning

confidence: 99%

“…The ascertainment probability is of the form a j = const·r j ε [Stene, 1977[Stene, , 1978Ewens and Shute, 1986], where r j is the number of AN members in the jth pedigree, when the whole pedigree is included in the pedigree sample frame (PSF; the subset of the pedigree members that can be probands) [see Elston and Sobel, 1979], or r j is the number of AN offspring, if pedigrees are ascertained via offspring-proband. The ε value determines a particular ascertainment scheme, wherein ε = 0 corresponds to complete ascertainment, while ε = 1 and 2 represent single and quadratic ascertainments, respectively [Ewens and Shute, 1986].…”

Section: Samples Analyzedmentioning

confidence: 99%

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Sample size required for predefined linkage decision quality

Ginsburg

Axenovich

1997

Genet. Epidemiol.

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Section: Results and Discussion Required Sample Sizementioning

confidence: 99%

Section: Samples Analyzedmentioning

confidence: 99%

Sample size required for predefined linkage decision quality

Ginsburg

Axenovich

1997

Genet. Epidemiol.

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“…It is assumed that when families are ascertained through an affected or unaffected parent, the probability of a family being included in the sample as a family of a case proband (where the proband is an affected parent) is proportional to y the number of affected parents in the family and the probability of a family being included as the family of a control proband (an unaffected parent) is proportional to (2 -y) the number of unaffected parents. This 'mode of ascertainment' is a variant of what geneticists refer to as single ascertainment [Stene, 1977;Hodge and Vieland, 1996] and which GBB [1967] has shown is implicit in epidemiologic approaches to familial aggregation. Following the notation of GBB [1967] given that a family is of size s, let '+' denote the event that a family in the population is included in the sample as the family of a case proband and we let '-' denote the event that a family in the population is included in the sample as the family of a control proband.…”

Section: Methodsmentioning

confidence: 99%

Approaches to Familial Aggregation: Hypothesis Testing and Estimation when Families Are Selected through Parent Probands under a Variant of Single Ascertainment

Wickramaratne¹

2004

Hum Hered

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Epidemiologic approaches to testing and estimating familial aggregation of a disease consist of comparing rates of disease in relatives of individuals with the disease (known as case probands) with rates of disease in relatives of individuals without the disease (known as control probands). Gold et al. (J Am Stat Ass 1967;62: 409–420) derived an explicit mathematical model and sampling methods, under which this approach is equivalent to testing the null hypotheses that the disease risk in families is homogenous. A basic assumption of this model is that every family member has the same risk of disease and that disease status is independent among family members, although the disease risk may vary between families. When the disease is suspected of having a genetic component, rather than being purely environmental, this model has been shown to be appropriate for detecting disease aggregation in siblings, when relatives are siblings of probands. This model however is unrealistic for use in nuclear families when the affected status of offspring is not independent of the affected status of parents, and these families are selected through an affected or an unaffected parent, so that a parent is the proband and relatives are offspring of probands. We extend the Gold et al. model to allow for the disease risk in offspring to vary with the affected status of the parent. We assume that families are selected through affected and unaffected parents, under a variation of single ascertainment. Under this study design, we show that the usual test of association between affected status of probands and relatives, performed by comparing sample proportions of affected relatives of affected and unaffected probands, respectively, is no longer equivalent to a test of homogeneity of disease risk in offspring. Instead, it is equivalent to testing that the disease risk in offspring is independent of the number of affected parents. This test reduces to a test of homogeneity if and only if one assumes that the variation in disease risk in offspring, between families, is solely due to the variation in the number of affected parents. As a result, we show that under this study design, the standard χ² test must be modified in order to obtain a valid test of familial aggregation. In addition the sample proportions of affected relatives of case and control probands, respectively, are shown to provide unbiased estimates of the expected risk of disease in an offspring given an affected/unaffected parent. We apply these results to methods of sample selection and discuss the practical implications of these findings.

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“…Morton [1959] described a simple model of ascertainment, which many investigators have used. Others [e.g., Stene, 1977;Greenberg, 19861 have described different models. Many authors [e.g., Morton, 1984;Greenberg, 19861 have documented the serious bias that can result when the wrong ascertainment model is assumed.…”

Section: Ascertain Men Tmentioning

confidence: 99%

Lods, wrods, and mods: The interpretation of lod scores calculated under different models

Hodge

Elston

1994

Genetic Epidemiology

127

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In this paper we examine the relationships among classical lod scores, "wrod" scores (lod scores calculated under the wrong genetic model), and "mod" scores (lod scores maximized over genetic model parameters). We compare the behavior of these scores when the state of nature is linkage to their behavior when the state of nature is no linkage. We describe sufficient conditions for mod scores to be valid and discuss their use to determine the correct genetic model. We show that lod scores represent a likelihood-ratio test for independence. We explain the "ascertainment-assumption-free" aspect of using mod scores to determine mode of inheritance and we set this aspect into a well-established statistical framework. Finally, we summarize practical guidelines for the use of mod scores.

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Assumptions for Different Ascertainment Models in Human Genetics

Cited by 33 publications

References 3 publications

Sample size required for predefined linkage decision quality

Sample size required for predefined linkage decision quality

Approaches to Familial Aggregation: Hypothesis Testing and Estimation when Families Are Selected through Parent Probands under a Variant of Single Ascertainment

Lods, wrods, and mods: The interpretation of lod scores calculated under different models

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