Studying time to pregnancy by use of a retrospective design

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

Studying time to pregnancy by use of a retrospective design. / Joffe, Michael; Key, Jane; Best, Nicky; Keiding, Niels; Scheike, Thomas; Jensen, Tina Kold.

In: American Journal of Epidemiology, Vol. 162, No. 2, 2005, p. 115-24.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Joffe, M, Key, J, Best, N, Keiding, N, Scheike, T & Jensen, TK 2005, 'Studying time to pregnancy by use of a retrospective design', American Journal of Epidemiology, vol. 162, no. 2, pp. 115-24. https://doi.org/10.1093/aje/kwi172

APA

Joffe, M., Key, J., Best, N., Keiding, N., Scheike, T., & Jensen, T. K. (2005). Studying time to pregnancy by use of a retrospective design. American Journal of Epidemiology, 162(2), 115-24. https://doi.org/10.1093/aje/kwi172

Vancouver

Joffe M, Key J, Best N, Keiding N, Scheike T, Jensen TK. Studying time to pregnancy by use of a retrospective design. American Journal of Epidemiology. 2005;162(2):115-24. https://doi.org/10.1093/aje/kwi172

Author

Joffe, Michael ; Key, Jane ; Best, Nicky ; Keiding, Niels ; Scheike, Thomas ; Jensen, Tina Kold. / Studying time to pregnancy by use of a retrospective design. In: American Journal of Epidemiology. 2005 ; Vol. 162, No. 2. pp. 115-24.

Bibtex

@article{c271c0b09ea911debc73000ea68e967b,
title = "Studying time to pregnancy by use of a retrospective design",
abstract = "Biologic fertility can be measured using time to pregnancy (TTP). Retrospective designs, although lacking detailed timed information about behavior and exposure, are useful since they have a well-defined target population, often have good response rates, and are simpler and less expensive to conduct than prospective studies. This paper reviews retrospective TTP studies from a methodological viewpoint and shows how methodological problems can be avoided or minimized by appropriate study design, conduct, and analysis. Sensitivity analyses using data from four European retrospective TTP studies are presented to explore the issues. Although the identified biases tend to have small impacts, the effects are not systematic across studies, and sensitivity analyses are recommended routinely. Planning bias can be checked by comparing propensity to report contraceptive failures in different exposure groups. Medical intervention bias can be avoided by censoring and inclusion of unsuccessful pregnancy attempts. Truncation bias can be a serious problem if unrecognized, but it is avoidable with appropriate study design and/or analysis. Behavior change bias can be minimized by assessing the covariates at the beginning of unprotected intercourse. More complete inference is possible if the study design covers the whole population, not just those who achieve a pregnancy.",
author = "Michael Joffe and Jane Key and Nicky Best and Niels Keiding and Thomas Scheike and Jensen, {Tina Kold}",
note = "Keywords: Bias (Epidemiology); Cohort Studies; Cross-Sectional Studies; Female; Fertility; Fertilization; Humans; Infertility; Male; Maternal Age; Pregnancy; Pregnancy, Unplanned; Research Design; Retrospective Studies; Smoking; Time Factors",
year = "2005",
doi = "10.1093/aje/kwi172",
language = "English",
volume = "162",
pages = "115--24",
journal = "American Journal of Epidemiology",
issn = "0002-9262",
publisher = "Oxford University Press",
number = "2",

}

RIS

TY - JOUR

T1 - Studying time to pregnancy by use of a retrospective design

AU - Joffe, Michael

AU - Key, Jane

AU - Best, Nicky

AU - Keiding, Niels

AU - Scheike, Thomas

AU - Jensen, Tina Kold

N1 - Keywords: Bias (Epidemiology); Cohort Studies; Cross-Sectional Studies; Female; Fertility; Fertilization; Humans; Infertility; Male; Maternal Age; Pregnancy; Pregnancy, Unplanned; Research Design; Retrospective Studies; Smoking; Time Factors

PY - 2005

Y1 - 2005

N2 - Biologic fertility can be measured using time to pregnancy (TTP). Retrospective designs, although lacking detailed timed information about behavior and exposure, are useful since they have a well-defined target population, often have good response rates, and are simpler and less expensive to conduct than prospective studies. This paper reviews retrospective TTP studies from a methodological viewpoint and shows how methodological problems can be avoided or minimized by appropriate study design, conduct, and analysis. Sensitivity analyses using data from four European retrospective TTP studies are presented to explore the issues. Although the identified biases tend to have small impacts, the effects are not systematic across studies, and sensitivity analyses are recommended routinely. Planning bias can be checked by comparing propensity to report contraceptive failures in different exposure groups. Medical intervention bias can be avoided by censoring and inclusion of unsuccessful pregnancy attempts. Truncation bias can be a serious problem if unrecognized, but it is avoidable with appropriate study design and/or analysis. Behavior change bias can be minimized by assessing the covariates at the beginning of unprotected intercourse. More complete inference is possible if the study design covers the whole population, not just those who achieve a pregnancy.

AB - Biologic fertility can be measured using time to pregnancy (TTP). Retrospective designs, although lacking detailed timed information about behavior and exposure, are useful since they have a well-defined target population, often have good response rates, and are simpler and less expensive to conduct than prospective studies. This paper reviews retrospective TTP studies from a methodological viewpoint and shows how methodological problems can be avoided or minimized by appropriate study design, conduct, and analysis. Sensitivity analyses using data from four European retrospective TTP studies are presented to explore the issues. Although the identified biases tend to have small impacts, the effects are not systematic across studies, and sensitivity analyses are recommended routinely. Planning bias can be checked by comparing propensity to report contraceptive failures in different exposure groups. Medical intervention bias can be avoided by censoring and inclusion of unsuccessful pregnancy attempts. Truncation bias can be a serious problem if unrecognized, but it is avoidable with appropriate study design and/or analysis. Behavior change bias can be minimized by assessing the covariates at the beginning of unprotected intercourse. More complete inference is possible if the study design covers the whole population, not just those who achieve a pregnancy.

U2 - 10.1093/aje/kwi172

DO - 10.1093/aje/kwi172

M3 - Journal article

C2 - 15972942

VL - 162

SP - 115

EP - 124

JO - American Journal of Epidemiology

JF - American Journal of Epidemiology

SN - 0002-9262

IS - 2

ER -

ID: 14359772