Adjustment for misclassification in studies of familial aggregation of disease using routine register data

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Standard

Adjustment for misclassification in studies of familial aggregation of disease using routine register data. / Andersen, Elisabeth Anne Wreford; Andersen, Per Kragh.

I: Statistics in Medicine, Bind 21, Nr. 23, 15.12.2002, s. 3595-607.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Andersen, EAW & Andersen, PK 2002, 'Adjustment for misclassification in studies of familial aggregation of disease using routine register data', Statistics in Medicine, bind 21, nr. 23, s. 3595-607. https://doi.org/10.1002/sim.1319

APA

Andersen, E. A. W., & Andersen, P. K. (2002). Adjustment for misclassification in studies of familial aggregation of disease using routine register data. Statistics in Medicine, 21(23), 3595-607. https://doi.org/10.1002/sim.1319

Vancouver

Andersen EAW, Andersen PK. Adjustment for misclassification in studies of familial aggregation of disease using routine register data. Statistics in Medicine. 2002 dec. 15;21(23):3595-607. https://doi.org/10.1002/sim.1319

Author

Andersen, Elisabeth Anne Wreford ; Andersen, Per Kragh. / Adjustment for misclassification in studies of familial aggregation of disease using routine register data. I: Statistics in Medicine. 2002 ; Bind 21, Nr. 23. s. 3595-607.

Bibtex

@article{d5d24073b1894d8e80521cb5b8442b12,

title = "Adjustment for misclassification in studies of familial aggregation of disease using routine register data",

abstract = "This paper discusses the misclassification that occurs when relying solely on routine register data in family studies of disease clustering. A register study of familial aggregation of schizophrenia is used as an example. The familial aggregation is studied using a regression model for the disease in the child including the disease status of the parents as a risk factor. If all the information is found in the routine registers then the disease status of the parents is only known from the time when the register started and if this information is used unquestioningly the parents who have had the disease before this time are misclassified as disease-free. Two methods are presented to adjust for this misclassification: regression calibration and an EM-type algorithm. These methods are used in the schizophrenia example where the large effect of having a schizophrenic mother hardly shows any signs of bias due to misclassification. The methods are also studied in simulations showing that the misclassification problem increases with the disease frequency.",

keywords = "Adolescent, Bias (Epidemiology), Case-Control Studies, Cluster Analysis, Computer Simulation, Denmark, Female, Humans, Male, Models, Statistical, Mothers, Registries, Regression Analysis, Risk Factors, Schizophrenia",

author = "Andersen, {Elisabeth Anne Wreford} and Andersen, {Per Kragh}",

year = "2002",

month = dec,

day = "15",

doi = "10.1002/sim.1319",

language = "English",

volume = "21",

pages = "3595--607",

journal = "Statistics in Medicine",

issn = "0277-6715",

publisher = "JohnWiley & Sons Ltd",

number = "23",

}

RIS

TY - JOUR

T1 - Adjustment for misclassification in studies of familial aggregation of disease using routine register data

AU - Andersen, Elisabeth Anne Wreford

AU - Andersen, Per Kragh

PY - 2002/12/15

Y1 - 2002/12/15

N2 - This paper discusses the misclassification that occurs when relying solely on routine register data in family studies of disease clustering. A register study of familial aggregation of schizophrenia is used as an example. The familial aggregation is studied using a regression model for the disease in the child including the disease status of the parents as a risk factor. If all the information is found in the routine registers then the disease status of the parents is only known from the time when the register started and if this information is used unquestioningly the parents who have had the disease before this time are misclassified as disease-free. Two methods are presented to adjust for this misclassification: regression calibration and an EM-type algorithm. These methods are used in the schizophrenia example where the large effect of having a schizophrenic mother hardly shows any signs of bias due to misclassification. The methods are also studied in simulations showing that the misclassification problem increases with the disease frequency.

AB - This paper discusses the misclassification that occurs when relying solely on routine register data in family studies of disease clustering. A register study of familial aggregation of schizophrenia is used as an example. The familial aggregation is studied using a regression model for the disease in the child including the disease status of the parents as a risk factor. If all the information is found in the routine registers then the disease status of the parents is only known from the time when the register started and if this information is used unquestioningly the parents who have had the disease before this time are misclassified as disease-free. Two methods are presented to adjust for this misclassification: regression calibration and an EM-type algorithm. These methods are used in the schizophrenia example where the large effect of having a schizophrenic mother hardly shows any signs of bias due to misclassification. The methods are also studied in simulations showing that the misclassification problem increases with the disease frequency.

KW - Adolescent

KW - Bias (Epidemiology)

KW - Case-Control Studies

KW - Cluster Analysis

KW - Computer Simulation

KW - Denmark

KW - Female

KW - Humans

KW - Male

KW - Models, Statistical

KW - Mothers

KW - Registries

KW - Regression Analysis

KW - Risk Factors

KW - Schizophrenia

U2 - 10.1002/sim.1319

DO - 10.1002/sim.1319

M3 - Journal article

C2 - 12436458

VL - 21

SP - 3595

EP - 3607

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 0277-6715

IS - 23

ER -

ID: 32106409