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An Introduction To Epidemiologic Methods
Published in Michele Kiely, Reproductive and Perinatal Epidemiology, 2019
Carol J. R. Hogue, George L. Rubin, Kenneth F. Schulz
Relative risk (risk ratio, rate ratio) is the ratio of the incidence risk or rate of outcome in the exposed group to the incidence risk or rate of outcome in the nonexposed group.3
Rate Ratios and Differences
Published in Peter Cummings, Analysis of Incidence Rates, 2019
In many studies, the choice between estimating a rate ratio or a rate difference may not matter. It may often be possible, when two groups are compared, to present the rates or adjusted rates for both groups; this seems like good practice when it can be done. The choice of then estimating a rate difference or ratio may be immaterial. In some studies, it may be possible to estimate both, which presents readers with two summaries of the data. This might be useful, for example, for future meta-analysts, who might prefer one scale over the other (Deeks 2002).
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Published in Filomena Pereira-Maxwell, Medical Statistics, 2018
Or simply, rate ratio. The ratio between the incidence rates experienced by the exposed and unexposed groups (or treated vs. control) in a follow-up study. For rare events, the rate ratio is a good approximation to the risk and odds ratios. See also relative risk, measures of effect.
Epidemiology of injuries in elite male and female futsal: a systematic review and meta-analysis
Published in Science and Medicine in Football, 2021
Iñaki Ruiz-Pérez, Alejandro López-Valenciano, José Ll Elvira, Alberto García-Gómez, Mark De Ste Croix, Francisco Ayala
Comparisons between factors were then made using a spreadsheet for combining effect statistics (Hopkins 2007), whereby the incidence rate ratio (and its associated confidence limits) were assessed against predetermined thresholds. An incidence rate ratio of 0.91 represented a substantially lower injury risk, while an incidence rate ratio of 1.10 indicated a substantially higher injury risk (Hopkins 2010). An effect was deemed unclear if its confidence interval overlapped the thresholds for substantiveness; that is, if the effect could be substantial in both a positive and negative sense. Otherwise, the effect was clear and deemed to have the magnitude of the largest observed likelihood value. This was qualified with a probabilistic term using the following scale: <0.5%, most unlikely; 0.5–5%, very unlikely; 5–25%, unlikely; 25–75%, possible; 75–95%, likely; 95–99.5%, very likely; >99.5%, most likely (Batterham and Hopkins 2006; Hopkins 2007).
Response to letter to the editor
Published in The Physician and Sportsmedicine, 2020
Hayden P. Baker, Kenneth Young-Hoon Lee, Steven R. Dayton, Michael A. Terry, Vehniah K. Tjong
In this letter to the editor the author notes potential concerns with the calculation of the rate ratio methodology utilized in our study. We agree that there was an error calculating the rate ratio. We also agree that the rate ratio provided in the letter to the editor is correct. Furthermore, we correctly calculated the relative risk of injury during Thursday night football games versus weekend games to corroborate the reported rate ratio in the letter to the editor. To correctly calculate the relative risk, we used the reported 419 injuries sustained during Thursday night football games as our number of events in the exposed group. To calculate the number of non-events in our exposed group we multiplied the number of Thursday night games included in the study (69) by the number of active players per game (53) and by the number of teams playing in each game (2); after subtracting the number of injuries from the non-events in our exposed group our calculated number of non-events was 6895. We repeated this methodology for the control group and found 9,201 injuries in the non-exposed group with 119,165 non-events in the non-exposed group. We then calculated the relative risk, which was RR = 0.80 with a 95% CI (0.72–0.88). These results are consistent with the reported risk ratio in the letter to the editor. Furthermore, these findings support our conclusions that Thursday Night Football games are not associated with higher reported injury rates when compared with weekend games.
Fall episodes in elderly patients with asthma and COPD – A pilot study
Published in Journal of Asthma, 2019
Andrzej Bozek, Jerzy Jarzab, Ewa Hadas, Marek Jakalski, Giorgio Walter Canonica
Descriptive analysis was used, and the Mann–Whitney U test was used to compare the groups of participants. The rate of falls was shown as an incidence ratio. The total number of falls reported by all participants was divided by the sum of person–years of observation, giving the mean number of falls per person per year of follow-up in the two groups analyzed. The incidence rate ratio is interpreted in a similar fashion to an odds ratio. Falls incidence rate ratios (frr) with 95% confidence intervals (CI) for each individual predictor variable were presented. Univariate analyses were based on negative binomial regression, with falls as a dependent variable according to Iinattiniemi et al. [14]. In this analysis, the following parameters were used: inhaled medications that were used for asthma or COPD by participants during observation, the total number of all used drugs in the same time, a number of comorbidities with the specification for their types, FEV1, categories of age, and the results of Berg Balance questionnaire (described above).