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Is an odds ratio of 1 Significant?
Statistical Significance If an odds ratio (OR) is 1, it means there is no association between the exposure and outcome. So, if the 95% confidence interval for an OR includes 1, it means the results are not statistically significant.
What does it mean when CI crosses 1?
Confidence interval
Confidence interval (CI) The confidence interval indicates the level of uncertainty around the measure of effect (precision of the effect estimate) which in this case is expressed as an OR. If the confidence interval crosses 1 (e.g. 95%CI 0.9-1.1) this implies there is no difference between arms of the study.
What is the interpretation when OR 1?
OR >1 indicates increased occurrence of an event. OR <1 indicates decreased occurrence of an event (protective exposure) Look at CI and P-value for statistical significance of value (Learn more about p values and confidence intervals here) In rare outcomes OR = RR (RR = Relative Risk).
How do you calculate odds ratio and p-value in Excel?
The formula =EXP(SUMPRODUCT(I28:I30,LN(H28:H30))/I31) is used to calculate the alternative common odds ratio in cell H31. The value of p (cell I31) is calculated by =SUM(I28:I30) where p1 (in cell I28) is calculated by the formula =1/SUMPRODUCT(1/B4:E4).
What is the p-value for 95 confidence?
0.05
The 95% confidence interval tells us clearly whether the difference is statistically significant or not. This means, in a concrete example, that if the lower limit of the confidence interval lay exactly at zero, then the p value would be 0.05.
How to calculate the odds of a positive outcome?
Odds = P (positive) / 1 – P (positive) = (42/90) / 1- (42/90) = (42/90) / (48/90) = 0.875 Thus, the odds ratio for experiencing a positive outcome under the new treatment compared to the existing treatment can be calculated as: Odds Ratio = 1.25 / 0.875 = 1.428.
How to interpret odds ratios, confidence intervals and p values?
This is a very basic introduction to interpreting odds ratios, confidence intervals and p values only and should help healthcare students begin to make sense of published research, which can initially be a daunting prospect.
How to interpret odds ratios, statology, and statistics?
Odds Ratio = 1.25 / 0.875 = 1.428. We would interpret this to mean that the odds that a patient experiences a positive outcome using the new treatment are 1.428 times the odds that a patient experiences a positive outcome using the existing treatment.
How is the odds ratio used to determine risk?
The odds ratio can also be used to determine whether a particular exposure is a risk factor for a particular outcome, and to compare the magnitude of various risk factors for that outcome. OR=1 Exposure does not affect odds of outcome