Odds Ratio Standard Error
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or absence of property B in a given population. If each individual in a population either does or does not have a property "A", (e.g. "high blood pressure"), and also either does or does not have a property "B" (e.g. odds ratio confidence interval crosses 1 "moderate alcohol consumption") where both properties are appropriately defined, then a ratio can be formed odds ratio confidence interval calculator which quantitatively describes the association between the presence/absence of "A" (high blood pressure) and the presence/absence of "B" (moderate alcohol consumption) for individuals
Risk Ratio Confidence Interval
in the population. This ratio is the odds ratio (OR) and can be computed following these steps: For a given individual that has "B" compute the odds that the same individual has "A" For a given individual that does
Confidence Interval Crosses 0
not have "B" compute the odds that the same individual has "A" Divide the odds from step 1 by the odds from step 2 to obtain the odds ratio (OR). The term "individual" in this usage does not have to refer to a human being, as a statistical population can measure any set of entities, whether living or inanimate. If the OR is greater than 1, then having "A" is considered to be "associated" with having "B" in odds ratio confidence interval p value calculator the sense that the having of "B" raises (relative to not-having "B") the odds of having "A". Note that this does not establish that B is a contributing cause of "A": it could be that the association is due to a third property, "C", which is a contributing cause of both "A" and "B" (confounding). The two other major ways of quantifying association are the risk ratio ("RR") and the absolute risk reduction ("ARR"). In clinical studies and many other settings, the parameter of greatest interest is often actually the RR, which is determined in a way that is similar to the one just described for the OR, except using probabilities instead of odds. Frequently, however, the available data only allows the computation of the OR; notably, this is so in the case of case-control studies, as explained below. On the other hand, if one of the properties (say, A) is sufficiently rare (the "rare disease assumption"), then the OR of having A given that the individual has B is a good approximation to the corresponding RR (the specification "A given B" is needed because, while the OR treats the two properties symmetrically, the RR and other measures do not). In a more technical language, the OR is a measure of effect size, describing the strength of association or non-independence between two binary data values. It is used as a descrip
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How To Report Odds Ratios And Confidence Intervals
more about Stack Overflow the company Business Learn more about hiring developers or posting confidence interval for odds ratio logistic regression ads with us Cross Validated Questions Tags Users Badges Unanswered Ask Question _ Cross Validated is a question and answer site confidence interval for odds ratio in r for people interested in statistics, machine learning, data analysis, data mining, and data visualization. Join them; it only takes a minute: Sign up Here's how it works: Anybody can ask a question Anybody can https://en.wikipedia.org/wiki/Odds_ratio answer The best answers are voted up and rise to the top How to calculate SE of an odds ratio up vote 0 down vote favorite If one is calculating odds ratio with a,b,c and d counts, I believe variance of log(OR) is given by var_log_OR = (1/a + 1/b + 1/c + 1/d) Hence one can calculate 95% confidence intervals of OR as follows: SE_log_OR = sqrt(var_log_OR) CI_lower_log_OR http://stats.stackexchange.com/questions/156597/how-to-calculate-se-of-an-odds-ratio = log(OR) - 1.96*SE_log_OR CI_upper_log_OR = log(OR) + 1.96*SE_log_OR CI_lower_OR = exp(CI_lower_log_OR) CI_upper_OR = exp(CI_upper_log_OR) But how can we calculate SE of OR? standard-error odds-ratio share|improve this question asked Jun 12 '15 at 1:39 rnso 2,74721131 add a comment| 3 Answers 3 active oldest votes up vote 3 down vote accepted @FrankHarrell is right that the standard error for an odds ratio is a problematic number in the sense that you can do better by testing on the corresponding log(odds ratio) scale, as the sampling distribution of the log(odds ratio) is more likely to be normally distributed. Nonetheless, the standard error of the odds ratio does exist, even if it is not that useful. One possible estimate is to use the delta method to move from the standard error of the log(odds ratio) to an approximation of the standard error of the odds ratio. $\sqrt{(1/a + 1/b + 1/c + 1/d)}\times\frac{a\times d}{b\times c}$ share|improve this answer answered Jun 12 '15 at 7:29 Maarten Buis 11.8k932 add a comment| up vote 2 down vote OR is not a valid quantity to compute a SE of in the sense that it cannot have a symmetric distribution. Applying +/- SE to it may lead to negative ORs. share|improve th
meansComparisonofproportionsRelative riskOdds ratioDiagnostictestvaluation Free statistical calculators Odds ratio calculator Cases with https://www.medcalc.org/calc/odds_ratio.php positive (bad) outcome Number in exposed group: a https://www.researchgate.net/post/Calculating_standard_error_of_a_log_Odds_ratio_from_confidence_intervals2 Number in control group: c Cases with negative (good) outcome Number in exposed group: b Number in control group: d Computational notes The odds ratio (OR), its standard error and confidence interval 95% confidence interval are calculated according to Altman, 1991. The odds ratio is given by with the standard error of the log odds ratio being and 95% confidence interval Where zeros cause problems with computation of the odds ratio or its standard error, ratio confidence interval 0.5 is added to all cells (a, b, c, d) (Pagano & Gauvreau, 2000; Deeks & Higgins, 2010). Test of significance: the P-value is calculated according to Sheskin, 2004 (p. 542). Literature Altman DG (1991) Practical statistics for medical research. London: Chapman and Hall. Altman DG, Deeks JJ, Sackett DL. Odds ratios should be avoided when events are common [letter]. BMJ 1998;317:1318. Deeks JJ, Higgins JPT (2010) Statistical algorithms in Review Manager 5. Retrieved from http://ims.cochrane.org/revman/documentation/Statistical-methods-in-RevMan-5.pdf Pagano M, Gauvreau K (2000) Principles of biostatistics. 2nd ed. Belmont, CA: Brooks/Cole. Parshall MB (2013) Unpacking the 2 x 2 table. Heart & Lung 42:221-226. [Abstract]Sheskin DJ (2004) Handbook of parametric and nonparametric statistical procedures. 3rd ed. Boca Raton: Chapman & Hall /CRC. Privacy & cookies Contact Site map ©1993-2016MedCalcSoftwarebvba
error of a log Odds ratio from confidence intervals? Higher limit of C.I - lower limit of C.I / 3.92 is the formula I used, my question is that this gives me a standard error of the regular odds ratio as opposed as the Log odds ratio, so should I just calculate the natural log of the standard errors I get through the above formula or should I first convert the limits of the confidence intervals into their natural log and calculate the S.E then? Topics E-Learning for Epidemiology & Statistics × 45 Questions 8,878 Followers Follow Community Health × 212 Questions 19,378 Followers Follow Epidemiology and Public Health × 626 Questions 33,794 Followers Follow Public Health × 690 Questions 115,142 Followers Follow Cancer Epidemiology × 54 Questions 2,704 Followers Follow Nov 18, 2013 Share Facebook Twitter LinkedIn Google+ 0 / 0 All Answers (1) Jason Leung · The Chinese University of Hong Kong For your formula, higher limit and lower limit of Ci should be taken natural log first e.g. CI of OR (2, 5), after taking natural log, it is (0.693, 1.609), SE=(1.609-0.693)/3.92=0.2337 remark: 3.92 is 1.96*2 Nov 18, 2013 Can you help by adding an answer? Add your answer Question followers (11) See all Jason Leung The Chinese University of Hong Kong Sachin Dhande Indian Council of Medical Research Mona Ellaithi Eik Vettorazzi University Medical Center Hamburg - Eppendorf Ivan E Perez Zohaib Khan Leibniz Institute for Prevention Research and Epidemiology – BIPS Haneen Khreis University of Leeds Tibor Kiss Ruhr-Universität Bochum Yusuf Cem Kaplan Izmir Katip Celebi Universitesi Ahmed Mahmoud University of Florida Views 4573 Followers 11 Answers 1 © 2008-2016 researchgate.net. All rights reserved.About us · Contact us · Careers · Developers · News · Help Center · Privacy · Terms · Copyright | Advertising · Recruiting We use cookies to give you the best possible experience on ResearchGate. Read our cookies policy to learn more.OkorDiscover by subject areaRecruit researchersJoin for freeLog in EmailPasswordForgot password?Keep me logged inor log in with ResearchGate is the professional network for scientists and researchers. Got a question you need answered quickly? Technical questions like the one you've just found usually get answered within 48 hours on ResearchGate. Sign up today to jo