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Questions tagged [odds-ratio]

A measure of association between two binary variables equal to the odds of a 'positive' outcome in 1 variable divided by the odds in the other. The OR ranges (0, infinity). It has a strong connection to logistic regression.

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Logistic Regression in R (Odds Ratio)

I'm trying to undertake a logistic regression analysis in R. I have attended courses covering this material using STATA. I am finding it very difficult to replicate ...
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Why do my p-values differ between logistic regression output, chi-squared test, and the confidence interval for the OR?

I have built a logistic regression where the outcome variable is being cured after receiving treatment (Cure vs. No Cure). All ...
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Poisson regression to estimate relative risk for binary outcomes

Brief Summary Why is it more common for logistic regression (with odds ratios) to be used in cohort studies with binary outcomes, as opposed to Poisson regression (with relative risks)? Background ...
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Interpretation of simple predictions to odds ratios in logistic regression

I'm somewhat new to using logistic regression, and a bit confused by a discrepancy between my interpretations of the following values which I thought would be the same: exponentiated beta values ...
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Help me understand adjusted odds ratio in logistic regression

I've been having a hard time trying to understand the use of logistic regression in a paper. The paper available here uses logistic regression to predict probability of complications during cataract ...
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20 votes
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logit - interpreting coefficients as probabilities

I seem to be missing some vital piece of information. I am aware that the coefficient of logistic regression are in log(odds), called the logit scale. Therefore to interpret them, ...
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Negative coefficient in ordered logistic regression

Suppose we have the ordinal response $y:\{\text{Bad, Neutral, Good}\} \rightarrow \{1,2,3\}$ and a set of variables $X:=[x_1,x_2,x_3]$ that we think will explain $y$. We then do an ordered logistic ...
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2 answers
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Does it make sense to use Logistic regression with binary outcome and predictor?

I have a binary outcome variable {0,1} and a predictor variable {0,1}. My thoughts are that it doesn't make sense to do logistic unless I include other variables and calculate the odds ratio. With ...
kms's user avatar
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Why do odds ratios from formula and R's fisher.test differ? Which one should one choose?

In the following example ...
winerd's user avatar
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18 votes
2 answers
22k views

Calculating risk ratio using odds ratio from logistic regression coefficient

I have a binary logistic regression with just one binary fixed factor predictor. The reason I don't do it as a Chi square or Fisher's exact test is that I also have a number of random factors (there ...
Amorphia's user avatar
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17 votes
4 answers
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What is the distribution of OR (odds ratio)?

I have a bunch of articles presenting "OR" with a- 95% CI (confidence intervals). I want to estimate from the articles the P value for the observed OR. For that, I need an assumption regarding the ...
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How do I calculate the standard deviation of the log-odds?

I have in my notes that the standard deviation of log odds is given by the $$\sqrt{(1/a + 1/b + 1/c + 1/d)}$$ I know that the derivation of this requires the Delta Method, but I'm not familiar with ...
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Different ways to produce a confidence interval for odds ratio from logistic regression

I am studying how to construct a 95% confidence interval for odds ratio from the coefficients obtained in the logistic regression. So, considering the logistic regression model, $$ \log\left(\frac{p}{...
Márcio Augusto Diniz's user avatar
15 votes
1 answer
1k views

Is meta-analysis of odds ratios essentially hopeless?

In a recent paper Norton et al. (2018)$^{[2]}$ state that Different odds ratios from the same study cannot be compared when the statistical models that result in odds ratio estimates have different ...
COOLSerdash's user avatar
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Is there any functional difference between an odds ratio and hazard ratio?

In logistic regression, an odds ratio of 2 means that the event is 2 time more probable given a one-unit increase in the predictor. In Cox regression, a hazard ratio of 2 means the event will occur ...
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How to conduct a meta-analysis on studies that report results variously as odds ratios, hazards ratios, or rate ratios?

I'm doing a meta-analysis of some studies that report results variously as odds ratios, hazards ratios or rate ratios (all with confidence intervals). Is there any way to combine these together/...
Mark Greenaway's user avatar
13 votes
5 answers
69k views

Converting odds ratio to percentage increase / reduction

Suppose I have a scenario like this : For every 1-point increase in X, odds ratio of event Y happening is 0.80 Does that mean the same as 'For every 1-point increase in X, odds of event Y happening ...
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How to calculate Odds ratio and 95% confidence interval for logistic regression for the following data?

I have the following data from a Research paper: S1 : n = 30 / Rest : n = 66 SH 11 / 8 For this to calculate p-value I have done it like following: <...
stack_learner's user avatar
12 votes
1 answer
42k views

adjusted odds ratio vs odds ratio

In multivariate regression analysis, it seems that people use different definitions of adjusted odds ratios. Could you please clarify for me what an adjusted OR is and how it differs from a non-...
dav's user avatar
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11 votes
2 answers
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Odds and odds ratios in logistic regression

I am having difficulties understanding one logistic regression explanation. The logistic regression is between temperature and fish which die or do not die. The slope of a logistic regression is 1....
Eddie's user avatar
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2 answers
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Exponentiated logistic regression coefficient different than odds ratio

As I understand it, the exponentiated beta value from a logistic regression is the odds ratio of that variable for the dependent variable of interest. However, the value does not match the manually ...
mike's user avatar
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11 votes
2 answers
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Interpretation of the Fisher-exact test

I'm running some R code, where I would like to check if some data is independent. I could use a Chi-square test, which rejects independence. However I would like to ...
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Odds ratio vs probability ratio

An odds is the ratio of the probability of an event to its complement: $$\text{odds}(X) = \frac{P(X)}{1-P(X)}$$ An odds ratio (OR) is the ratio of the odds of an event in one group (say, $A$) versus ...
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10 votes
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Interpreting logistic regression coefficients with a regularization term

I understand the coefficients of a logistic equation can be interpreted as odd ratio. If a regularization term is added to control for over-fitting, how does this change the interpretation of the ...
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Does the "divide by 4 rule" give the upper bound marginal effect?

In the logisitic regression chapter of "Data Analysis Using Regression and Multilevel/Hierarchical Models" by Gelman and Hill, The "Divide by 4" rule is presented to approximate average marginal ...
Michael Webb's user avatar
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9 votes
3 answers
622 views

Odds Ratios paradox? Pooled OR inconsistent with subgroup ORs

I have two groups (A and B) that each produce ORs of 1.44 and 1.50. However, if I combine the frequencies for the two groups to create a pooled dataset, I get an OR of 1.40. I get that it's not going ...
S Robidoux's user avatar
9 votes
1 answer
39k views

Relation between logistic regression coefficient and odds ratio in JMP

From the output of a logistic regression in JMP, I read about two binary variables: Var1 estimate -0.1007384 Var2 estimate 0.21528927 and then ...
glassy's user avatar
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9 votes
1 answer
17k views

Converting odds ratios to Cohen's d for meta analysis

I'm conducting a meta-analysis largely on mean differences data, however I have several articles that report only an odds ratio, N, p value, and confidence interval, and I need to convert this ...
Erica's user avatar
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9 votes
4 answers
12k views

How to calculate confidence intervals for pooled odd ratios in meta-analysis?

I have two datasets from genome-wide association studies. The only information available are the odd ratios and their confidence intervals (95%) for each genotyped SNP. My want to generate a forest ...
BIBB's user avatar
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9 votes
2 answers
3k views

Citation for Statistical test for difference between two odds ratios?

In a comment here, @gung wrote, I believe they can overlap a little (maybe ~25%) & still be significant at the 5% level. Remember that the 95% CI you see is for the individual OR, but the test ...
cpjh10's user avatar
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9 votes
3 answers
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Interpreting coefficients in a logistic regression model with a categorical variable having more than 2 levels

There is quite some content online interpreting odds in a logistic model with a dichotomous predictor. My problem is understanding coefficients when there are more than 2 levels for a categorical ...
Maddy's user avatar
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9 votes
3 answers
2k views

Meta analysis on studies with 0-frequency cells

I am familiar with meta analysis and meta regression techniques (using the R package metafor from Viechtbauer), but I recently stumbled on a problem I can't easily ...
Joris Meys's user avatar
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9 votes
1 answer
18k views

Manually calculating logistic regression coefficient

I am taking this short example from wiki:https://en.wikipedia.org/wiki/Logistic_regression ...
user2542275's user avatar
9 votes
0 answers
2k views

After oversampling/undersampling is it always appropriate to adjust probabilities using the odds ratio regardless of the sampling method used?

I have an imbalanced dataset where the target class is <1% of sample. I apply oversampling or undersampling e.g. https://github.com/scikit-learn-contrib/imbalanced-learn. I run random forest on ...
simon's user avatar
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8 votes
3 answers
64k views

How to interpret odds ratio?

Suppose we have a baseline exposure group and 2 other exposure groups for a case control study. Suppose the odds ratio for the first exposure is $1.5$ and the odds ratio for the second exposure is $1....
guestguy's user avatar
8 votes
1 answer
6k views

What does "case-control" and "cross-sectional" mean in the context of logistic modeling?

While studying logistic modeling, I read the following statement The fact that only odds ratios, not individual risks, can be estimated from logistic modeling in case-control or cross-sectional ...
user3125's user avatar
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8 votes
1 answer
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Interpreting odds ratios less than 1 with 3-category outcome

I have a 3-category ordered outcome (food consumption: 1=no food, 2=less food, 3=more food) and a 3-category ordered predictor (food exposure: 3=no time, 2= less time, 1= more time- whereby 3=no time ...
Andreea's user avatar
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7 votes
2 answers
12k views

How can I explain proportional odds models to a layman?

I'm writing an interdisciplinary research paper and I'm having some troubles in clearly explaining my findings. In particular, I applied a proportional odds model with one regressor $x$ and three ...
stochazesthai's user avatar
7 votes
3 answers
3k views

Log odds ratio - what happens if linearity fails?

I haven't found much info on this by googling so i thought maybe someone where has some answers for me. When it comes to binary logistic regression the model assumes that the log odds ratio has a ...
Janono's user avatar
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1 answer
2k views

Does confidence interval for odds ratio assume log-normal distribution?

The formula floating around for calculating 95% confidence interval of an odds ratio is: e^(log(OR) ± 1.96 x sqrt(1/a + 1/b + 1/c + 1/d)) Does one need to ...
Ray Zhang's user avatar
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7 votes
3 answers
2k views

Explaining Odds Ratio and Relative Risk to the statistically challenged

I'm peer-reviewing a manuscript for a psychology journal in which I believe the authors have mixed up odds-ratio and risk-ratio. They are being so stubborn in their insistence that they have not mixed ...
Amorphia's user avatar
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7 votes
1 answer
1k views

The odds ratio calculated in my regression model seems to be too high

I have conducted a within-subject experiment. The DV of the experiment is a categorical variable (0 or 1) and the IV has three levels (1 = none, 2 = weak, 3 = strong) Since the DV is binary, I've ...
Kihyo's user avatar
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7 votes
1 answer
697 views

Interpreting zero odds ratio from Fisher's exact test

I did fisher's exact test and I got an odds ratio equal to zero. Can you please clarify what it means? I want to plot the odds ratio but don't know how to deal with the zero and INF values. below are ...
Marwah Al-kaabi's user avatar
7 votes
2 answers
1k views

Understanding Odds Ratios in Logistic Regression

I'm trying to understand how to interpret log odds ratios in logistic regression. Let's say I have the following output: ...
ATMathew's user avatar
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7 votes
5 answers
15k views

How to convert sport odds into percentage?

I am wondering how to convert sport odds to the percentage format. There's this example: ...
user984621's user avatar
7 votes
1 answer
207 views

Where is my mistake in this definition of Bayes Factor?

From "The Bayesian Choice" by Christian P. Robert. The definition of the Bayes factor is given to be the ratio of the posterior probabilities of the null and the alternative hypothesis over the ratio ...
Quality's user avatar
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7 votes
1 answer
2k views

Why is the Bayes factor sometimes considered more important than the Posterior Odds?

To the best of my knowledge, the posterior odds satisfies the equation: $$(\text{posterior odds}) = (\text{Bayes factor}) \times (\text{prior odds}) $$ This is a simple consequence of Bayes' rule. The ...
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7 votes
1 answer
11k views

Dealing with 0 in cell count for Fisher's exact test

Control Cases A 0 2 B 1000 298 I am dealing with 0 in my 2x2 tables, and I was wondering what are some of my options when it comes to ...
Adrian's user avatar
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7 votes
1 answer
1k views

Bayes theorem in odds form - incorrect in Tetlock's 'Superforecasting' book?

Page 170 in Philip Tetlock's et al. Superforecasting book shows Bayes' theorem in odds form as: $$\frac{P (H|D)}{P (\neg H|D)} = P (D|H) P (D|\neg H) \frac{ P (H)}{P (\neg H)}$$ Posterior Odds = ...
Thor's user avatar
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7 votes
1 answer
978 views

Combined odds ratio

I wonder if there's a way to calculate the combined odds ratio for certain SNPs in a meta-analysis of a several GWAS, even when you don't have the SE, neither beta, for each individual study? Thank ...
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