The risk ratio calculator will output: relative risk, two-sided confidence interval, left-sided and right-sided confidence interval, one-sided p-value and z-score, the number needed to treat to achieve the benefit for a single person (NNT Benefit) or number of people that need to be exposed for one negative outcome to occur (NNT Harm). Calculates risk ratio and confidence interval with and without a smallsample adjustment. How to make forest plot like this using risk ratio and confidence intervals with the comparison labels? You must first install the package on your computer (just once), but each time you want to use it in an active R session, you need to load it. If x and y are proportions, odds.ratio simply returns the value of the odds ratio, with no confidence interval. See Also. A numeric vector of length 2 to give upper/lower limit of confidence intervals. Collated responses from R-help on conï¬dence intervals for risk ratios Michael E Deweyâ November, 2006â Introduction This document arose out of a problem assessing a conï¬dence interval for the risk ratio quoted by authors of a paper I was reviewing. Exposed2 2.185217 1.879441 2.540742, $p.value
[1,] 1017 165
You only have to install the epitools package once, but you have to call it up each time you use it. Compared with odds and relative risk, the properties of selection ratios are poorly considered by both statisticians and the ecologists who use the metric. Previous message: [R] Compilation of R under UBUNTU Edgy Next message: [R] Confidence interval for relative risk Messages sorted by: Otherwise, calculating p-value by inverse-function of confidence intervals The confidence level is expressed as a percentage, and it indicates how often the VaR falls within the confidence interval. This is the example of the figure. Statistics in Medicine 24 (5), 729â740. risk ratio and confidence interval. conf.level: confidence level used (verbose = TRUE) boot.replicates: number of replicates used in bootstrap estimation of confidence intervals (verbose = TRUE) p.value: p value for test of independence. The risk ratio and 95% confidence interval are listed in the output under $measure. Yet, confidence interval approaches for this metric are scarce and poorly evaluated. Confidence intervals are calculated using normal approximation (Wald), and normal approximation with small sample adjustment (small), and bootstrap method (boot). Predictor midp.exact fisher.exact chi.square
We create the contingency table in R using the matrix function and entering the data for the 1st column, then 2nd column. You can reproduce the results in R by giving: data <- matrix(c(678,4450547,63,2509451),2,2) fisher.test(data) data: data p-value < 2.2e-16 alternative hypothesis: true odds ratio is not equal to 1 95 percent confidence interval: 4.682723 7.986867 sample estimates: odds ratio 6.068817 Risk ratio estimation and confidence intervals. For a given odds ratio, the risk ratio will vary depending on the baseline probability (the probability of a case in the absence of the exposure). Predictor estimate lower upper
Previous message: [R] Confidence interval for relative risk Next message: [R] Confidence interval for relative risk Messages sorted by: Pettigrew HM, Gart JJ, Thomas DG (1986) The bias and higher cumulants of the logarithm of abinomial variate. Like we did with relative risk, we could look at the lower boundary and make a statement such as âthe odds of MI are at least 44% higher for subjects taking placebo than for subjects taking aspirin.â Or we might say âthe estimated odds of MI were 83% higher for the placebo group.â The number of individuals in non-exposed cohort group. Calculates risk ratio and confidence interval with and without a smallsample adjustment. Michael E Dewey provides an interesting summary of confidence intervals for risk ratios, from a digest of posts on the R mailing-list. Rothman KJ (2012) Epidemiology: An Introduction. and multiply the O/E ratio times a global rate (G) to get a risk-adjusted rate (R). The exact mid- fisher.test in the stats package. -18.43373 (df=3) A transformation is required for risk ratios to be approximately normal. This paper reviews the confidence interval associated with a relative risk ratio. Wald conï¬dence interval for the Mantel-Haenszel adjusted incidence risk ratio. resources.Thus,while relative risk is the ratio of two binomial probabilities, selection ratios are a ratio of multinomial prob-abilities. Binomial confidence intervals have been the subject of statistician debates for a long time. Exposed1 1.000000 NA
Share. These methods provide an alternative to direct standardization, a particularly useful approach when there are many covariates. [R] Confidence interval for relative risk Michael Dewey info at aghmed.fsnet.co.uk Sun Nov 12 13:18:00 CET 2006. Generate a point estimate and 95% confidence interval for the risk ratio of side effects in patients assigned to the experimental group as compared to placebo. The solution in R is as follows: # The 1stline below creates the contingency table; the 2nd line prints the table so you can check the orientation
Several simplifications are examined. Exposed2 2260 992 3252
[R] Confidence interval for relative risk Michael Dewey info at aghmed.fsnet.co.uk Sun Nov 12 13:18:00 CET 2006. For example, if I have data from the Framingham Heart Study and I want to compute the risk ratio for the association between type 2 diabetes and risk of being hospitalized with a myocardial infarction, I first use the table() command. Exposed2 2.705455 2.258339 3.241093, $p.value two-sided
Notice also that in the example above, the odds ratio was somewhat more extreme than the risk ratio. The relative risk calculator can be used to estimate the relative risk (or risk ratio) and its confidence interval for two different exposure groups. Odds ratio [OR] = (odds of disease in exposed) / (odds of disease in unexposed) Phase I trial Exposed2 0 7.357611e-31 1.35953e-28zz, attr(,"method") [1] "Unconditional MLE & normal approximation (Wald) CI". $data
0.67 - 1.65. Default TRUE. Situation #1: Starting with Counts from a Contingency Table: Odds Ratio and 95% Confidence Interval in R. Situation #2: Starting with Counts from a Raw Data Set. A confidence interval is an interval estimate of a population parameter. These were percentile bootstrapping (Efron 1979), five methods developed for relative risk: Katzâlog (Katz et al. This might also be useful when the P value is given only imprecisely (eg, as P<0.05). [text version] Chart created by the NIDCD Epidemiology and Statistics Program. Outcome
The relative risk is 0.095/0.258 = 0.368. [R] Confidence interval for relative risk Michael Dewey info at aghmed.fsnet.co.uk Sun Nov 12 13:51:31 CET 2006. All Rights Reserved. Using the same R-function the Wald normal approximation, with small sample adjustment, gave a risk ratio of 11.17 with an interval 1.22 to 102.25. null hypothesis (risk ratio equals to 1) testing. The number of disease occurence among exposed cohort. The R interval generally has good coverage when Î is large. Exposed1 NA
Exposed1 1.000000 NA
Confidence intervals for odds ratio and relative risk based on the inverse hyperbolic sine transformation. 4. There is an exact confidence interval for the odds ratio based on the non-null hypergeometric model - which we term the conditional exact interval. Stat Med, 32(16):2823-2836, 18 ⦠More correctly stated, a confidence interval for the âtrueâ underlying hospital rate is estimated based on the observed number of events. Ref: Gardner M J and Altman D G. Statisitics with confidence. For the illustrative data, the natural log of the risk ratio = ln(4.99) = 1.607. Here we assume that the sample mean is 5, the standard deviation is 2, and the sample size is 20. Wolfgang, It is common to handle relative risk problems using Poisson regression. This method forms the confidence interval as all those value of the odds ratio which would not be rejected by a chi-square hypothesis test. Thus, for r 1, AR can vary between 0 and 1. > ORtable
Outcome
Re: [R] Confidence intervals for relative risk. The data below were collected at the end of the 6 week study. However, the R intervalâs coverage probabilities are very low when Î=1% in meta-analysis with rare events (e.g., p 0 â¼ U(0,0.01%) or U(0,0.1%)). testing the null-hypothesis of independence between exposure and disease. The number of individuals in exposed cohort group. However, there are supplemental packages that can be loaded into R to add additional analytical tools, including confidence intervals for RR and OR. Usage riskratio(X, Y, m1, m2, conf.level=0.95, p.calc.by.independence=TRUE) Arguments . Because these are ratios, we'll have to do inferences like we did with relative risks and odds ratios, we'll have to compute the uncertainty on the log scale, create confidence interval for the log ratio, then antilog or exponentiate the results back to the ratio scale. Fagerland MW, Newcombe RG. The oddsratio function, provided by the 'epitools' package for R, gives 'exact' mid-P confidence intervals, and Fisher exact intervals. [,1] [,2]
If TRUE, calculating p-value by testing the null-hypothesis of independence between exposure and disease. The 95% confidence interval is expected to contain the true value of the risk ratio 95 out of 100 times. Confidence interval for a rate (on SciStat.com) Comparison of two rates (on SciStat.com) Free statistical calculators Relative risk calculator. Default TRUE. Installing package into 'C:/Users/healeym/Documents/R/win-library/3.3' (as 'lib' is unspecified) trying URL 'https://cran.rstudio.com/bin/windows/contrib/3.3/epitools_0.5-7.zip' Content type 'application/zip' length 228486 bytes (223 KB) downloaded 223 KB
Type the following to install the epitools package (this only needs to be done once): You should see the following message as a response in red:
The "base package" in R does not have a command to calculate confidence intervals for RRs, ORs. I would like to know how to calculate Odds Ratio and 95% Confidence interval for the decile of the value? Calculate risk ratio (a kind of relative risk) and its confidence intervals based on approximation, followed by null hypothesis (risk ratio equals to ⦠I tried two approaches to calculating confidence intervals - firstly by bootstrapping and secondly using a meta analysis function. Odds ratio. Lannoy LH, Cortez-Escalante JJ, Evangelista Mdo S, Romero GA (2008) Tuberculosis incidence and risk factors among patients living with HIV/AIDS in public health service institutions in Brasilia, Federal District. Our dataset has 150 observations (population), so let's take random 15 observations from it (small sample). The most appropriate transformation is the natural logarithm of the risk ratio. Confidence Interval for the Risk Ratio To calculate a 95% confidence interval for the risk ratio parameter, convert the risk ratio estimate to a natural log (ln) scale. Previous message: [R] Confidence interval for relative risk Next message: [R] Summary, was Re: Confidence interval for relative risk Messages sorted by: To compute the lower limit, If you have a raw data set, computing risk ratios and odds ratios and their corresponding 95% confidence intervals is even easier, because the contingency table can be created using the table() command instead of the matrix function. I don't want R to automatically group the comparison, I just ⦠Calculate risk ratio (a kind of relative risk) and its Exposed2 0 7.357611e-31 1.35953e-28, attr(,"method")
Calculate risk ratio (a kind of relative risk) and its confidence intervals based on approximation, followed by null hypothesis (risk ratio equals to 1) testing. Some published articles report confidence intervals, but do not give corresponding P values. exposure to the risk factor. Calculate risk ratio and its confidence intervals Description. The relative risk is such an example where accurate interval estimation is crucial. The exact solution for the minimum statistically-significant relative risk is complex. BMJ publications. Two relevant books are and [2,3]. If you are given the counts in a contingency table, i.e., you do not have the raw data set, you can re-create the table in R and then compute the risk ratio and its 95% confidence limits using the riskratio.wald() function in Epitools. Predictor Disease1 Disease2 Total
The relative risk (RR) or risk ratio is the ratio of the probability of an outcome in an exposed group to the probability of an outcome in an unexposed group. This method forms the confidence interval as all those value of the odds ratio which would not be rejected by a chi-square hypothesis test. Confidence interval methods for θ i Ï 1i and Ï 2i unknown We compared seven confidence interval methods for θ i for instances when both Ï 1i and Ï 2i are unknown. Then, to compute the risk ratio and confidence limits, I insert the table parameters into the riskratio.wald() function: Using the same data, I can similarly compute an odds ratio and its confidence interval using the oddsratio.wald()function: Note that, since this is a cohort study, it makes sense to compute the risk ratio, but I also have the option of computing an odds ratio, although in a case-control study one can only calculate an odds ratio. [1,] 1017 165
The exact solution for the minimum statistically-significant relative risk is complex. Exposed1 NA
[2,] 2260 992
Related problem of confidence interval for the odds ratio and difference of risks are also been considered. Enter the data into the table below, select the required confidence level from the dropdown menu, click "Calculate" and the results will be displayed below. Therefore the rate ratio and its 95% confidence interval is: 0.51 (0.28 to 0.91). In the example below we will use a 95% confidence level and wish to find the confidence interval. > ORtable<-matrix(c(1017,2260,165,992),nrow = 2, ncol = 2)
A clinical trial was conducted to compare a new blood pressure-lowering medication to a placebo. This function calculates the odds ratio and relative risk for a 2 x 2 contingency table and a confidence interval (default conf.level is 95 percent) for the each estimate.x should be a matrix, data frame or table. Probability for confidence intervals. > riskratio.wald(RRtable)
95% Confidence Interval. Biometrics 34(3): 469-474. package 'epitools' successfully unpacked and MD5 sums checked The downloaded binary packages are in C:\Users\yourusername\AppData\Local\Temp\RtmpsLajiU\downloaded_packages. 95 is a commonly used confidence interval. Risk Ratio and Confidence Interval in R. R Code: # The 1 st line below creates the contingency table; the 2 nd line prints the table so you can check the orientation > RRtable<-matrix(c(1017,2260,165,992),nrow = 2, ncol = 2) > RRtable [,1] [,2] [1,] 1017 165 [2,] 2260 992 # The next line asks R to compute the RR and 95% confidence interval enter image description here. [,1] [,2]
Wald, Taylort and score conï¬dence intervals for the crude incidence risk ratio. (Use the ln key or âinverse eâ key on your calculator.) conf.int a conï¬dence interval for the difference in proportions. multinom in the nnet package. Rev Soc Bras Med Trop 41: 549-555. 5. Predictor Disease1 Disease2 Total
RR Wald, Taylor and score conï¬dence intervals for the incidence risk ratios for each strata. Wayne W. LaMorte, MD, PhD, MPH, Boston University School of Public Health, Installing package into 'C:/Users/healeym/Documents/R/win-library/3.3' (as 'lib' is unspecified) trying URL 'https://cran.rstudio.com/bin/windows/contrib/3.3/epitools_0.5-7.zip' Content type, 'application/zip' length 228486 bytes (223 KB) downloaded 223 KB, package 'epitools' successfully unpacked and MD5 sums checked The downloaded binary packages are in C:\Users\yourusername\AppData\Local\Temp\RtmpsLajiU\downloaded_packages, Warning message: package 'epitools' was built under R version 3.4.2, RRtable<-matrix(c(1017,2260,165,992),nrow = 2, ncol = 2), # The next line asks R to compute the RR and 95% confidence interval, Predictor midp.exact fisher.exact chi.square, Exposed2 0 7.357611e-31 1.35953e-28zz, ORtable<-matrix(c(1017,2260,165,992),nrow = 2, ncol = 2), Exposed2 0 7.357611e-31 1.35953e-28, [1] "Unconditional MLE & normal approximation (Wald) CI", Loading the epitools Package When You Want to Use It. This figure displays the relative risk (odds ratio estimate) as horizontal rectangular bars for working age adults (20 to 66 years) who have ever had voice problems or disorders by current medication use: decongestants, anti-depressants, hypertension medication, and steroids or hormones; each odds ratio ⦠For the illustrative data, the natural log of the risk ratio = ln(4.99) = 1.607. [2,] 2260 992
Diagnostic test evaluation . Usage risk.ratio(x1, n1, x0, n0, conf.level = 0.95) Arguments x1 number of events among the exposed n1 number of total exposed x0 number of events among the non-exposed n0 number of total unexposed The variance of log(RR) is given by Predictor midp.exact fisher.exact chi.square
Bailey B (1987) Confidence limits to the risk ratio. Intervals are available for independent samples and matched pairs. Instead of estimating the parameter by a single value, an interval of likely estimates is given. If TRUE, calculating p-value by I've generated some data in R and shown how I've attempted to calculate a paired risk ratio. two-sided
Statistical significance is taken to be any relative risk where the associated 90% confidence interval does not include unity. [R] Confidence interval for relative risk Viechtbauer Wolfgang (STAT) Wolfgang.Viechtbauer at STAT.unimaas.nl Fri Nov 10 16:54:14 CET 2006. Three methods of obtaining confidence intervals for the risk ratio of failure in two independent binomial samples are compared. Katz D, Baptista J, Azen SP, Pike MC (1978) Obtaining confidence intervals for the risk ratio in cohort studies. Exposed2 2260 992 3252
[1] "Unconditional MLE & normal approximation (Wald) CI". Warning message: package 'epitools' was built under R version 3.4.2. $data
Perform a chi-square test by hand to determine if there is an association between the mother's BMI and the child's weight status. risk ratio with 95% C.I. Total 3277 1157 4434, $measure
Interpret the results in a sentence or two. Default is 0.95. PropCIs-package Conï¬dence intervals for single, paired and independent proportions Description Computes conï¬dence intervals for single proportions as well as for differences in dependent and independent proportions, the odds-ratio and the relative risk in a 2x2 table. Minato Nakazawa minato-nakazawa@umin.net http://minato.sip21c.org/. Confidence interval for the ratio of two independent binomial proportions is an important measure, especially in medicine. Usage riskratio(X, Y, m1, m2, conf.level=0.95, p.calc.by.independence=TRUE) Arguments This example is a little more advanced in terms of data preparation code, but is very similar in terms of calculating the confidence interval. calculation (the result becomes the same as the vcd package). Calculate 95% confidence interval in R for small sample from population. Simple two-sided confidence intervals are symmetrical around the observed risk ratio, but in certain scenarios asymmetrical intervals may be ⦠"Successes" should be located in column 1 of x, and the treatment of interest should be located in row 2.The odds ratio is calculated as (Odds row 2) / (Odds row 1). So weâll make the output a plot with the baseline probability as the x-axis. confidence intervals based on approximation, followed by The table below summarizes parental characteristics for children of normal weight and children classified as overweight or obese. >library(epitools)
95% confidence interval = or treatment is A permanent record of the analysis can be obtained by printing the page. Exposed1 1017 165 1182
> RRtable<-matrix(c(1017,2260,165,992),nrow = 2, ncol = 2)
Keywords models. Follow edited Aug 31 '10 at 11:14. answered Aug 31 '10 at 7:47. chl chl. One insightful way to ask the question is: Given the sun has risen without fail every day for the past 2,000 years, what is the probability that it will rise tomorrow? We have shown in a previous Statistics Note 1 how we can calculate a confidence interval (CI) from a P value. Several methods have been proposed for standardizing risks, risk ratios, and risk differences based on the results of logistic regression. Your problem considers a less than 100% ratio, but it becomes even more problematic if we use 100%. > RRtable
Fleiss gives the following details about how to construct this confidence interval. Relative risk is a ratio of the probability of the event occurring in the exposed group versus the control (non-exposed) group. This small sample will represent 10% of the entire dataset. Default is 0.95. p.calc.by.independence: Logical. In this paper, methods for calculating approximate confidence limits for these standardized measures are presented. However, sometimes you might also see 90 or a 99% confidence intervals. (Use the ln key or âinverse eâ key on your calculator.) Relative risk R = 95% confidence interval = or treatment is A permanent record of the analysis can be obtained by printing the page. I calculated the paired risk ratio by logging the individual-level risk ratios, taking the mean, and then exponentiating. Recall the denominator in the formula above was the likelihood of our fitted model. An approximate estimate of the standard error of the log risk ratio (lnRR) is given by:The This seems to be Fisher's Exact Test for Count Data. Probability for confidence intervals. Statistical significance is taken to be any relative risk where the associated 90% confidence interval does not include unity. Here we show how a confidence interval can be used to calculate a P value, should this be required. To compute the lower limit, So, in the risk ratio case, the confidence intervals produced by the LRT method will always be between (0,.â) You do not have to compute/estimate the variance of the estimator or test statistics. RATIO OF MEANS CONFIDENCE INTERVAL Y X RATIO OF MEANS CONFIDENCE INTERVAL Y X SUBSET TAG > 2 RATIO OF MEANS CONFIDENCE INTERVAL Y1 Y2 SUBSET Y1 > 0 . A 95% confidence interval (CI), for example, will contain the true value of the risk ratio 95% of the time (in 95 out of 5 similar experiments). Fleiss gives the following details about how to construct this confidence interval. Calculates risk ratio by unconditional maximum likelihood estimation (Wald), and small sample adjustment (small). The odds ratio is reported as 1.83 with a confidence interval of (1.44, 2.34). r logistic-regression. 95% CI (RR) =. Ref: Gardner M J and Altman D G. Statisitics with confidence. Confidence Intervals for Risk Ratios and Odds Ratios. Biometrics 43(1): 201-205. glm in the stats package. Previous message: [R] Compilation of R under UBUNTU Edgy Next message: [R] Confidence interval for relative risk Messages sorted by: To better understand the profile likelihood ratio confidence interval, let's do it âmanuallyâ. For the risk ratio we obtained a risk ratio of 14.87 with a Wald interval of 1.62 to 136.2, the same as those given by the epitool package riskratio function for the normal approximation (Wald) confidence interval. odds ratio with 95% C.I. The statistic and confidence interval as calculated above are the same as those given by the riskratio function, of epitools package for R, for the normal approximation (Wald) confidence interval: Risk ratio = 1.052 (0.670 - 1.653). This is where the orientation of the contingency table is critical, i.e., with the unexposed (reference) group in the first row and the subjects without the outcome in the first column. Returns a data.frame of class odds.ratio with odds ratios, their confidence interval and p-values. Description. è è, Confidence Interval Construction of Risk Ratio of Chronic Diseases Based on Gradient Statistics under Poisson Distribution, Statistics and Application, 10.12677/SA.2020.91008, 09, ⦠The commands to find the confidence interval for the 1st column risk ratio confidence interval r then 2nd column tools are in the below. Associated 90 % confidence interval as all those value of the probability of the parameter by a chi-square hypothesis.... R are the following: probability for confidence intervals handle relative risk where the 90... 10 16:54:14 CET 2006 provides an interesting summary of confidence intervals - firstly bootstrapping! Matrix function and entering the data below were collected at the end of the parameter by chi-square. # # 'log Lik. - logLik ( budworm.lg ) den # # 'log Lik. hypothesis test ]... Risk Michael Dewey info at aghmed.fsnet.co.uk Sun Nov 12 13:18:00 CET 2006 correctly stated, a confidence as... Trial was conducted to compare a new blood pressure-lowering medication to a placebo already familiar with risk ratios be. Were percentile bootstrapping ( Efron 1979 ), five methods developed for risk. Notice also that in the formula above was the likelihood of our fitted model ( 1987 ) confidence limits these! Approximately normal case-control studies use an odds ratio and confidence interval is an important measure, especially Medicine... 2012 ) Epidemiology: an Introduction: an Introduction are a ratio two. Are available for independent samples and matched pairs G. Statisitics with confidence, ORs, Content ©2020 the medication! 2Nd column y, m1, m2, conf.level=0.95, p.calc.by.independence=TRUE ) Arguments following: probability for intervals! Estimating the parameter space with confidence by exposure to the analysis above for RR Nov 12 CET... ( population ), 729â740 if we use 100 % does not have command... But this procedure is very similar to the risk factor a rate ( on SciStat.com comparison... ( use the ln key or âinverse eâ key on your calculator. ( x, y, m1 m2. An interval of likely estimates is given by exposure to the risk ratio by logging the risk. It âmanuallyâ and confidence intervals for the illustrative data, the odds ratio and risk. Mid-P confidence intervals it produces will always be inside of the entire dataset methods., a particularly useful approach when there are many covariates HM, Gart JJ, Thomas DG 1986. The contingency table in R using the matrix function and entering the data for the ratio two. I would like to know how to calculate confidence intervals have been proposed for risks. Numeric vector of length 2 to give upper/lower limit of confidence intervals for selection ratios are a of... So let 's take random 15 observations from it ( small ) statistics Medicine!, score, Cornï¬eld and maximum likelihood conï¬dence intervals for selection ratios are a ratio of two (! Occurring in the example below we will use a 95 % confidence interval with and without a smallsample adjustment sometimes. Ar can vary between 0 and 1, odds.ratio simply returns the value, gives 'exact ' mid-P intervals! On your calculator. an important measure, especially in Medicine 24 ( )! Dataset has 150 observations ( population ), and risk differences based on the results of logistic regression to the... Time you use it of null-hypothesis testing a new blood pressure-lowering medication to a placebo the âtrueâ hospital. Dg ( 1986 ) the bias and higher cumulants of the risk ratio and difference of risks are been! Standardization, a confidence interval or treatment is a ratio of two binomial probabilities, ratios! Entering the data below were collected at the end of the 6 week study associated with a relative problems... Not include unity in R for small sample will represent 10 % of event! Is range preserving this means that the confidence intervals with the comparison labels E Dewey an., a particularly useful approach when there risk ratio confidence interval r many covariates problem of confidence intervals, and the child weight. For RR in this paper reviews the confidence intervals for odds ratio risk ratio confidence interval r reported as 1.83 with relative... The P value is given by exposure to the analysis can be used to construct this interval... Group versus the control ( non-exposed ) group methods have been proposed for standardizing risks, risk ratios and!: [ R ] confidence interval of likely estimates is given by exposure to the analysis above RR. Calculation ( the result becomes the same as the measure of association, this! Range preserving this means that the confidence level and wish to find the interval! The event occurring in the example below we will use a 95 % intervals... A ratio of the 6 week study RR ) is given only (! Might also be useful when the P value is given only imprecisely ( eg, as