Bias correction for estimates from linear excess relative risk models in small case‐control studies

2021 ◽  
Author(s):  
Sander Roberti ◽  
Flora E. Leeuwen ◽  
Michael Hauptmann ◽  
Ruth M. Pfeiffer
Keyword(s):  
Relative Risk ◽  
Bias Correction ◽  
Case Control ◽  
Excess Relative Risk ◽  
Case Control Studies ◽  
Risk Models

The results obtained from studies of causation

2017 ◽  
Author(s):  
Mark Elwood
Keyword(s):  
Relative Risk ◽  
Intervention Studies ◽  
Case Control ◽  
Risk Difference ◽  
Attributable Risk ◽  
Number Needed To Treat ◽  
Case Control Studies ◽  
Sampling Schemes ◽  
Multiplicative Models ◽  
The Relationship

This chapter shows the format and derivation of results from studies. Cohort and intervention studies yield relative risk and risk difference, also known as attributable risk, and number needed to treat (NNT). Count and person-time methods are shown. Additive and multiplicative models for two or more exposures are shown. Case-control studies give primarily odds ratio; the relationship between this and relative risk is explained. Different sampling schemes for case-control studies include methods were a case can also be a control. Surveys yield results similar to cohort studies.

scholarly journals Association between green tea intake and risk of gastric cancer: a systematic review and dose–response meta-analysis of observational studies

2017 ◽  
Vol 20 (17) ◽  
pp. 3183-3192 ◽  
Author(s):  
Yanhong Huang ◽  
Hongru Chen ◽  
Liang Zhou ◽  
Gaoming Li ◽  
Dali Yi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Systematic Review ◽  
High Temperature ◽  
Relative Risk ◽  
Green Tea ◽  
Dose Response ◽  
Observational Studies ◽  
Meta Analysis ◽  
Case Control ◽  
Case Control Studies

AbstractObjectiveTo examine and quantify the potential dose–response relationship between green tea intake and the risk of gastric cancer.DesignWe searched PubMed, EMBASE, Web of Science, CBM, CNKI and VIP up to December 2015 without language restrictions.SettingA systematic review and dose–response meta-analysis of observational studies.SubjectsFive cohort studies and eight case–control studies.ResultsCompared with the lowest level of green tea intake, the pooled relative risk (95 % CI) of gastric cancer was 1·05 (0·90, 1·21, I2=20·3 %) for the cohort studies and the pooled OR (95 % CI) was 0·84 (0·74, 0·95, I2=48·3 %) for the case–control studies. The pooled relative risk of gastric cancer was 0·79 (0·63, 0·97, I2=63·8 %) for intake of 6 cups green tea/d, 0·59 (0·42, 0·82, I2=1·0 %) for 25 years of green tea intake and 7·60 (1·67, 34·60, I2=86·5 %) for drinking very hot green tea.ConclusionsDrinking green tea has a certain preventive effect on reducing the risk of gastric cancer, particularly for long-term and high-dose consumption. Drinking too high-temperature green tea may increase the risk of gastric cancer, but it is still unclear whether high-temperature green tea is a risk factor for gastric cancer. Further studies should be performed to obtain more detailed results, including other gastric cancer risk factors such as smoking and alcohol consumption and the dose of the effective components in green tea, to provide more reliable evidence-based medical references for the relationship between green tea and gastric cancer.

Validity in estimating relative risk in case-control studies

1973 ◽  
Vol 26 (4) ◽  
pp. 219-225 ◽  
Author(s):  
Daniel G. Seigel ◽  
Samuel W. Greenhouse
Keyword(s):  
Relative Risk ◽  
Case Control ◽  
Case Control Studies

Estimating Relative Risk from Heterogeneous Strata

1988 ◽  
Vol 27 (03) ◽  
pp. 118-124 ◽  
Author(s):  
W. Ahlborn ◽  
H.-J. Tuz ◽  
K. Überla
Keyword(s):  
Relative Risk ◽  
Cohort Studies ◽  
Risk Measures ◽  
Logistic Models ◽  
Case Control ◽  
Asymptotic Distributions ◽  
Weight Functions ◽  
Risk Indicator ◽  
Case Control Studies ◽  
Special Cases

SummaryThe uncritical use of risk estimators can lead to serious bias. The estimation of overall risk ratios for heterogeneous strata and the weights used have been discussed recently. This paper starts with the definition of relative risk in the population, considering heterogeneous strata and a cofactor, using weight functions. From this general formula four different weight functions leading to four different overall measures of relative risk (RR1, RR1, RR3, RR4 ) are. derived as special cases. The estimability of the parameters in relation to the underlying sampling design is investigated. Consistent estimators are provided and the asymptotic distributions of the estimators are given for prospective cohort studies, case control studies with fixed strata and case control studies with given sample sizes. For some of the estimates the . asymptotic variances are given. It is shown that for case control studies with fixed strata neither the Mantel-Haenszel estimator nor another estimator of this class is consistent. An extension to more than two risk levels is provided and the relationships between various risk measures and other implications are commented on. A way is described to improve risk estimation by using information from the population. An example for cohort studies is given. Generally we propose to use RR3 , which lies between RR1 and RR2 and can be estimated more precisely using the sometimes available distribution of the cofactor in the population. If the relative risk across strata is heterogeneous, logistic models for the construction of a single risk indicator have some drawbacks.

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