jepcastel > Statistical models bias(epidemiology)

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1Treatment effects in the presence of unmeasured confounding: dealing with observations in the tails of the propensity score distribution--a simulation study.
T. Stürmer, K. Rothman, J. Avorn, und R. Glynn. American journal of epidemiology, 172 (7): 843-54 (Oktober 2010)5732<m:linebreak></m:linebreak>JID: 7910653; aheadofprint;<m:linebreak></m:linebreak>Propensity score.
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Bias(Epidemiology)
Calibration
CohortStudies
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SurvivalRate
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1Instrumental variables: application and limitations.
E. Martens, W. Pestman, A. de Boer, S. Belitser, und O. Klungel. Epidemiology (Cambridge, Mass.), 17 (3): 260-7 (Mai 2006)4042<m:linebreak></m:linebreak>Variables instrumentals.
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1Adjusting a relative-risk estimate for study imperfections.
G. Maldonado. Journal of epidemiology and community health, 62 (7): 655-63 (Juli 2008)4593<m:linebreak></m:linebreak>GR: 1R29-ES07986/ES/NIEHS NIH HHS/United States; JID: 7909766; ppublish;<m:linebreak></m:linebreak>Mesures d'associació.
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Algorithms
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1Survival analysis in total joint replacement: an alternative method of accounting for the presence of competing risk.
P. Fennema, und J. Lubsen. The Journal of bone and joint surgery. British volume, 92 (5): 701-6 (Mai 2010)5813<m:linebreak></m:linebreak>LR: 20101110; JID: 0375355; ppublish;<m:linebreak></m:linebreak>Anàlisi de supervivència; Competing risks.
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1Equivalence of the mediation, confounding and suppression effect.
D. MacKinnon, J. Krull, und C. Lockwood. Prevention science : the official journal of the Society for Prevention Research, 1 (4): 173-81 (Dezember 2000)3530<m:linebreak></m:linebreak>Mesures d'associació.
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1Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders.
T. Vanderweele, und O. Arah. Epidemiology (Cambridge, Mass.), 22 (1): 42-52 (Januar 2011)6262<m:linebreak></m:linebreak>LR: 20110412; GR: R03 HD060696-01A1/HD/NICHD NIH HHS/United States; JID: 9009644; NIHMS239676; OID: NLM: NIHMS239676 Available on 01/01/12; OID: NLM: PMC3073860 Available on 01/01/12; PMCR: 2012/01/01; ppublish;.
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1Accounting for independent nondifferential misclassification does not increase certainty that an observed association is in the correct direction.
S. Greenland, und P. Gustafson. American journal of epidemiology, 164 (1): 63-8 (Juli 2006)4381<m:linebreak></m:linebreak>PUBM: Print-Electronic; DEP: 20060426; JID: 7910653; 2006/04/26 aheadofprint; ppublish;<m:linebreak></m:linebreak>Mesures d'associació.
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1Designs for the combination of group- and individual-level data.
S. Haneuse, und S. Bartell. Epidemiology (Cambridge, Mass.), 22 (3): 382-9 (Mai 2011)6098<m:linebreak></m:linebreak>Review; NLM Journal Code: a2t, 9009644;.
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1Marginal Structural Models: unbiased estimation for longitudinal studies.
E. Moodie, und D. Stephens. International journal of public health, 56 (1): 117-9 (Februar 2011)6250<m:linebreak></m:linebreak>GR: Canadian Institutes of Health Research/Canada; JID: 101304551; 2010/05/07 received; 2010/09/12 accepted; 2010/08/01 revised; 2010/10/08 aheadofprint; ppublish;<m:linebreak></m:linebreak>Propensity score; Marginal structural models; Introductori.
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1Remarks on the method of propensity score.
J. Pearl. Statistics in medicine, 28 (9): 1415-6; author reply 1420-3 (April 2009)5208<m:linebreak></m:linebreak>JID: 8215016; CON: Stat Med. 2007 Jan 15;26(1):20-36. PMID: 17072897; CON: Stat Med. 2008 Jun 30;27(14):2740-1; author reply 2741-2. PMID: 18069729; ppublish;<m:linebreak></m:linebreak>Propensity score.
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RCT
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1How far from non-differential does exposure or disease misclassification have to be to bias measures of association away from the null?
A. Jurek, S. Greenland, und G. Maldonado. International journal of epidemiology, 37 (2): 382-5 (April 2008)4980<m:linebreak></m:linebreak>LR: 20081121; JID: 7802871; 2008/01/09 aheadofprint; ppublish;.
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1Randomizing research participants: promoting balance and concealment in small samples.
E. Matthews, P. Cook, M. Terada, und M. Aloia. Research in nursing & health, 33 (3): 243-53 (Juni 2010)5642<m:linebreak></m:linebreak>CI: (c) 2010; GR: 1UL1RR025780-01/RR/NCRR NIH HHS/United States; GR: NR010587/NR/NINR NIH HHS/United States; GR: NR04817/NR/NINR NIH HHS/United States; JID: 7806136; ppublish;<m:linebreak></m:linebreak>Aleatorització.
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Bias(Epidemiology)
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Humans
Models
RandomizedControlledTrialsasTopic:statistics
SampleSize
Statistical
RCT
Bias(Epidemiology)BiometryBiometry:methodsHumansModelsRandomizedControlledTrialsasTopic:statisticsSampleSizeStatisticalRCT
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1Bias formulas for external adjustment and sensitivity analysis of unmeasured confounders.
O. Arah, Y. Chiba, und S. Greenland. Annals of epidemiology, 18 (8): 637-46 (August 2008)4616<m:linebreak></m:linebreak>JID: 9100013; 2007/09/14 received; 2008/03/10 revised; 2008/04/02 accepted; ppublish;<m:linebreak></m:linebreak>Mesures d'associació.
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Bias(Epidemiology)
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Humans
Models
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OddsRatio
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Statistical
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1Proper interpretation of non-differential misclassification effects: expectations vs observations.
A. Jurek, S. Greenland, G. Maldonado, und T. Church. International journal of epidemiology, 34 (3): 680-7 (Juni 2005)3939<m:linebreak></m:linebreak>Mesures d'associació.
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Bias(Epidemiology)
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ComputerSimulation
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Models
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Risk
Software
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1Bias and heteroscedastic memory error in self-reported health behavior: an investigation using covariance structure analysis.
E. Kupek. BMC medical research methodology, 2 (1): 14 (November 2002)2926<m:linebreak></m:linebreak>Mesures d'associació.
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SexualPartners
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1Goodness-of-fit diagnostics for the propensity score model when estimating treatment effects using covariate adjustment with the propensity score.
P. Austin. Pharmacoepidemiology and drug safety, 17 (12): 1202-17 (Dezember 2008)4693<m:linebreak></m:linebreak>CI: Copyright (c) 2008; JID: 9208369; ppublish;<m:linebreak></m:linebreak>Propensity score.
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Adrenergicbeta-Antagonists
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1Multiple attacks from multiple perspectives.
D. Redelmeier. Journal of clinical epidemiology, 59 (9): 871-2 (September 2006)4773<m:linebreak></m:linebreak>LR: 20061115; JID: 8801383; CON: J Clin Epidemiol. 2006 Sep;59(9):964-9. PMID: 16895820; 2006/03/05 received; 2006/03/12 accepted; 2006/06/19 aheadofprint; ppublish;.
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1Addressing the issue of channeling bias in observational studies with propensity scores analysis.
F. Lobo, S. Wagner, C. Gross, und J. Schommer. Research in social & administrative pharmacy : RSAP, 2 (1): 143-51 (März 2006)6524<m:linebreak></m:linebreak>LR: 20071115; JID: 101231974; ppublish;<m:linebreak></m:linebreak>Propensity score; Introductori.
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1Reducing bias through directed acyclic graphs.
I. Shrier, und R. Platt. BMC medical research methodology, (Januar 2008)5089<m:linebreak></m:linebreak>JID: 100968545; OID: NLM: PMC2601045; 2008/03/11 received; 2008/10/30 accepted; 2008/10/30 aheadofprint; epublish;<m:linebreak></m:linebreak>Mesures d'associació.
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1Combining ecological and individual variables to reduce confounding by indication: case study--subarachnoid hemorrhage treatment.
S. Johnston. Journal of clinical epidemiology, 53 (12): 1236-41 (Dezember 2000)2724<m:linebreak></m:linebreak>Mesures d'associació.
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1Treatment effects in the presence of unmeasured confounding: dealing with observations in the tails of the propensity score distribution--a simulation study.

1Instrumental variables: application and limitations.

1Adjusting a relative-risk estimate for study imperfections.

1Survival analysis in total joint replacement: an alternative method of accounting for the presence of competing risk.

1Equivalence of the mediation, confounding and suppression effect.

1Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders.

1Accounting for independent nondifferential misclassification does not increase certainty that an observed association is in the correct direction.

1Designs for the combination of group- and individual-level data.

1Marginal Structural Models: unbiased estimation for longitudinal studies.

1Remarks on the method of propensity score.

1How far from non-differential does exposure or disease misclassification have to be to bias measures of association away from the null?

1Randomizing research participants: promoting balance and concealment in small samples.

1Bias formulas for external adjustment and sensitivity analysis of unmeasured confounders.

1Proper interpretation of non-differential misclassification effects: expectations vs observations.

1Bias and heteroscedastic memory error in self-reported health behavior: an investigation using covariance structure analysis.

1Goodness-of-fit diagnostics for the propensity score model when estimating treatment effects using covariate adjustment with the propensity score.

1Multiple attacks from multiple perspectives.

1Addressing the issue of channeling bias in observational studies with propensity scores analysis.

1Reducing bias through directed acyclic graphs.

1Combining ecological and individual variables to reduce confounding by indication: case study--subarachnoid hemorrhage treatment.

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