Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease
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Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease. / Dyson, Greg; Frikke-Schmidt, Ruth; Nordestgaard, Børge G; Tybjaerg-Hansen, Anne; Sing, Charles F.
In: Genetic Epidemiology, Vol. 33, No. 4, 2009, p. 317-24.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease
AU - Dyson, Greg
AU - Frikke-Schmidt, Ruth
AU - Nordestgaard, Børge G
AU - Tybjaerg-Hansen, Anne
AU - Sing, Charles F
N1 - Keywords: Aged; Algorithms; Apolipoproteins E; Confidence Intervals; Databases, Factual; Denmark; Environment; Epidemiologic Methods; Humans; Lipoprotein Lipase; Longitudinal Studies; Male; Middle Aged; Models, Statistical; Myocardial Ischemia; Polymorphism, Single Nucleotide; Prospective Studies; Risk Factors
PY - 2009
Y1 - 2009
N2 - This article extends the Patient Rule-Induction Method (PRIM) for modeling cumulative incidence of disease developed by Dyson et al. (Genet Epidemiol 31:515-527) to include the simultaneous consideration of non-additive combinations of predictor variables, a significance test of each combination, an adjustment for multiple testing and a confidence interval for the estimate of the cumulative incidence of disease in each partition. We employ the partitioning algorithm component of the Combinatorial Partitioning Method to construct combinations of predictors, permutation testing to assess the significance of each combination, theoretical arguments for incorporating a multiple testing adjustment and bootstrap resampling to produce the confidence intervals. An illustration of this revised PRIM utilizing a sample of 2,258 European male participants from the Copenhagen City Heart Study is presented that assesses the utility of genetic variants in predicting the presence of ischemic heart disease beyond the established risk factors.
AB - This article extends the Patient Rule-Induction Method (PRIM) for modeling cumulative incidence of disease developed by Dyson et al. (Genet Epidemiol 31:515-527) to include the simultaneous consideration of non-additive combinations of predictor variables, a significance test of each combination, an adjustment for multiple testing and a confidence interval for the estimate of the cumulative incidence of disease in each partition. We employ the partitioning algorithm component of the Combinatorial Partitioning Method to construct combinations of predictors, permutation testing to assess the significance of each combination, theoretical arguments for incorporating a multiple testing adjustment and bootstrap resampling to produce the confidence intervals. An illustration of this revised PRIM utilizing a sample of 2,258 European male participants from the Copenhagen City Heart Study is presented that assesses the utility of genetic variants in predicting the presence of ischemic heart disease beyond the established risk factors.
U2 - 10.1002/gepi.20383
DO - 10.1002/gepi.20383
M3 - Journal article
C2 - 19025787
VL - 33
SP - 317
EP - 324
JO - Genetic Epidemiology
JF - Genetic Epidemiology
SN - 0741-0395
IS - 4
ER -
ID: 20569208