Thus, P( [sample mean] - margin of error < < [sample mean] + margin of error) = 0.95. Compute the confidence interval for Ln(RR) using the equation above. We emphasized that in case-control studies the only measure of association that can be calculated is the odds ratio. If you do a two-sided level 0.05 test of hypothesis that the relative risk is different from 1 and get a p-value less than 0.05 then this is equivalent to a two-sided 95% confidence interval that does not contain 1. D We can now substitute the descriptive statistics on the difference scores and the t value for 95% confidence as follows: So, the 95% confidence interval for the difference is (-12.4, 1.8). In other words, the standard error of the point estimate is: This formula is appropriate for large samples, defined as at least 5 successes and at least 5 failures in the sample. Nevertheless, one can compute an odds ratio, which is a similar relative measure of effect.6 (For a more detailed explanation of the case-control design, see the module on case-control studies in Introduction to Epidemiology). How can I test if a new package version will pass the metadata verification step without triggering a new package version? confidence interval for the Question: Using the subsample in the table above, what is the 90% confidence interval for BMI? The null value is 1. Consider again the randomized trial that evaluated the effectiveness of a newly developed pain reliever for patients following joint replacement surgery. For more information on mid-$p$, you can refer to. As far as I know, there's no reference to relative risk in Selvin's book (also referenced in the online help). review. Based on this sample, we are 95% confident that the true systolic blood pressure in the population is between 113.3 and 129.1. We now ask you to use these data to compute the odds of pain relief in each group, the odds ratio for patients receiving new pain reliever as compared to patients receiving standard pain reliever, and the 95% confidence interval for the odds ratio. It is also possible, although the likelihood is small, that the confidence interval does not contain the true population parameter. If there are fewer than 5 successes or failures then alternative procedures, called exact methods, must be used to estimate the population proportion.1,2. e [9][10] To find the confidence interval around the RR itself, the two bounds of the above confidence interval can be exponentiated.[9]. These formulas assume equal variability in the two populations (i.e., the population variances are equal, or 12= 22), meaning that the outcome is equally variable in each of the comparison populations. Here I want to show the progressive change in the relative risk and NOT meta-analysis. However, the samples are related or dependent. How to Calculate Odds Ratio and Relative Risk in Excel, How to Create a Horizontal Legend in Base R (2 Methods), VBA: How to Merge Cells with the Same Values, VBA: How to Use MATCH Function with Dates. The confidence intervals for the difference in means provide a range of likely values for (1-2). Therefore, computing the confidence interval for a risk ratio is a two step procedure. Date last modified: October 27, 2017. Using the subsample in the table above, what is the 90% confidence interval for BMI? t values are listed by degrees of freedom (df). Two-sided confidence intervals for the single proportion: Comparison of seven methods. Find the confidence interval for the relative risk. When samples are matched or paired, difference scores are computed for each participant or between members of a matched pair, and "n" is the number of participants or pairs, is the mean of the difference scores, and Sd is the standard deviation of the difference scores, In the Framingham Offspring Study, participants attend clinical examinations approximately every four years. Together with risk difference and odds ratio, relative risk measures the association between the exposure and the outcome. Learn more about Stack Overflow the company, and our products. A 95% confidence interval for Ln(RR) is (-1.50193, -0.14003). Thus, under the rare disease assumption, In practice the odds ratio is commonly used for case-control studies, as the relative risk cannot be estimated.[1]. A total of 100 participants completed the trial and the data are summarized below. log What kind of tool do I need to change my bottom bracket? Proportion: Whats the Difference? Note that for a given sample, the 99% confidence interval would be wider than the 95% confidence interval, because it allows one to be more confident that the unknown population parameter is contained within the interval. The confidence interval for the difference in means provides an estimate of the absolute difference in means of the outcome variable of interest between the comparison groups. ( The sample size is n=10, the degrees of freedom (df) = n-1 = 9. A larger margin of error (wider interval) is indicative of a less precise estimate. If not, then alternative formulas must be used to account for the heterogeneity in variances.3,4. When there are small differences between groups, it may be possible to demonstrate that the differences are statistically significant if the sample size is sufficiently large, as it is in this example. The point estimate of prevalent CVD among non-smokers is 298/3,055 = 0.0975, and the point estimate of prevalent CVD among current smokers is 81/744 = 0.1089. {\displaystyle z_{\alpha }} But the ARR is higher and the NNT lower in people with higher absolute risks. To compute the confidence interval for an odds ratio use the formula. Is this how to convert odds ratio intervals to risk ratios, Relative Risk, confidence interval and sample size relationship. However, if the sample size is large (n > 30), then the sample standard deviations can be used to estimate the population standard deviation. Since the sample size is large, we can use the formula that employs the Z-score. In contrast, when comparing two independent samples in this fashion the confidence interval provides a range of values for the difference. The outcome of interest was all-cause mortality. Probability vs. Statology Study is the ultimate online statistics study guide that helps you study and practice all of the core concepts taught in any elementary statistics course and makes your life so much easier as a student. We will again arbitrarily designate men group 1 and women group 2. Use MathJax to format equations. Relative Risk = 0.25 / 0.024 = 10.4. This way the relative risk can be interpreted in Bayesian terms as the posterior ratio of the exposure (i.e. After completing this module, the student will be able to: There are a number of population parameters of potential interest when one is estimating health outcomes (or "endpoints"). How Prism computes the confidence interval of the relative risk risk. We often calculate relative risk when analyzing a 22 table, which takes on the following format: The relative risk tells us the probability of an event occurring in a treatment group compared to the probability of an event occurring in a control group. For example, we might be interested in the difference in an outcome between twins or between siblings. Next, we will check the assumption of equality of population variances. [3] As such, it is used to compare the risk of an adverse outcome when receiving a medical treatment versus no treatment (or placebo), or for environmental risk factors. NOTE that when the probability is low, the odds and the probability are very similar. The 95% confidence interval estimate for the relative risk is computed using the two step procedure outlined above. The parameter of interest is the mean difference, d. Now, for computing the $100(1-\alpha)$ CIs, this asymptotic approach yields an approximate SD estimate for $\ln(\text{RR})$ of $(\frac{1}{a_1}-\frac{1}{n_1}+\frac{1}{a_0}-\frac{1}{n_0})^{1/2}$, and the Wald limits are found to be $\exp(\ln(\text{RR}))\pm Z_c \text{SD}(\ln(\text{RR}))$, where $Z_c$ is the corresponding quantile for the standard normal distribution. New external SSD acting up, no eject option. Substituting the sample statistics and the t value for 95% confidence, we have the following expression: Interpretation: Based on this sample of size n=10, our best estimate of the true mean systolic blood pressure in the population is 121.2. This is statistically significant because the 95% confidence interval does not include the null value (OR=1.0). The Central Limit Theorem introduced in the module on Probability stated that, for large samples, the distribution of the sample means is approximately normally distributed with a mean: and a standard deviation (also called the standard error): For the standard normal distribution, P(-1.96 < Z < 1.96) = 0.95, i.e., there is a 95% probability that a standard normal variable, Z, will fall between -1.96 and 1.96. The point estimate of the odds ratio is OR=3.2, and we are 95% confident that the true odds ratio lies between 1.27 and 7.21. is then, where Consider the following hypothetical study of the association between pesticide exposure and breast cancer in a population of 6, 647 people. Since relative risk is a more intuitive measure of effectiveness, the distinction is important especially in cases of medium to high probabilities. Existence of rational points on generalized Fermat quintics. Remember that a previous quiz question in this module asked you to calculate a point estimate for the difference in proportions of patients reporting a clinically meaningful reduction in pain between pain relievers as (0.46-0.22) = 0.24, or 24%, and the 95% confidence interval for the risk difference was (6%, 42%). The confidence interval suggests that the relative risk could be anywhere from 0.4 to 12.6 and because it includes 1 we cannot conclude that there is a statistically significantly elevated risk with the new procedure. By convention we typically regard the unexposed (or least exposed) group as the comparison group, and the proportion of successes or the risk for the unexposed comparison group is the denominator for the ratio. In such a case, investigators often interpret the odds ratio as if it were a relative risk (i.e., as a comparison of risks rather than a comparison of odds which is less intuitive). So given the p-value of 0.049 you would expect that 1 would fall outside the interval. A 95% confidence interval of 1.46-2.75 around a point estimate of relative risk of 2.00, for instance, indicates that a relative risk of less than 1.46 or greater than 2.75 can be ruled out at the 95% confidence level, and that a statistical test of any relative risk outside the interval would yield a probability value less than 0.05. The relative risk calculator can be used to estimate the relative risk (or risk ratio) and its confidence interval for two different exposure groups. If data were available on all subjects in the population the the distribution of disease and exposure might look like this: If we had such data on all subjects, we would know the total number of exposed and non-exposed subjects, and within each exposure group we would know the number of diseased and non-disease people, so we could calculate the risk ratio. For example, in a study examining the effect of the drug apixaban on the occurrence of thromboembolism, 8.8% of placebo-treated patients experienced the disease, but only 1.7% of patients treated with the drug did, so the relative risk is .19 (1.7/8.8): patients receiving apixaban had 19% the disease risk of patients receiving the placebo. Thanks for the link on the R-help mailing list. The relative risk or risk ratio is given by with the standard error of the log relative risk being and 95% confidence interval {\displaystyle \scriptstyle \approx } Another way of thinking about a confidence interval is that it is the range of likely values of the parameter (defined as the point estimate + margin of error) with a specified level of confidence (which is similar to a probability). A 95% confidence interval for Ln(RR) is (-1.50193, -0.14003). [11] If the posterior ratio of exposure is similar to that of the prior, the effect is approximately 1, indicating no association with the disease, since it didn't change beliefs of the exposure. In practice, we select a sample from the target population and use sample statistics (e.g., the sample mean or sample proportion) as estimates of the unknown parameter. In other words, we don't know the exposure distribution for the entire source population. The incidence of moderate hypoxemia was 2.8% in the remimazolam group and 17.4% in the propofol group, with a statistically significant difference between the groups (relative risk [RR] = 0.161; 95% confidence interval [CI], 0.049 to 0.528; p < 0.001). The following table shows the number of players who passed and failed the skills test, based on the program they used: We would interpret this to mean that the probability that a player passes the test by using the new program are just 0.8718 times the probability that a player passes the test by using the old program. document.getElementById( "ak_js_1" ).setAttribute( "value", ( new Date() ).getTime() ); Statology is a site that makes learning statistics easy by explaining topics in simple and straightforward ways. In this example, we have far more than 5 successes (cases of prevalent CVD) and failures (persons free of CVD) in each comparison group, so the following formula can be used: So the 95% confidence interval is (-0.0133, 0.0361). [Note: Both the table of Z-scores and the table of t-scores can also be accessed from the "Other Resources" on the right side of the page. . {\displaystyle \log(RR)} Here smoking status defines the comparison groups, and we will call the current smokers group 1 and the non-smokers group 2. The point estimate for the relative risk is. Compute the confidence interval for Ln(RR) using the equation above. The sample size is denoted by n, and we let x denote the number of "successes" in the sample. Relative risk is used in the statistical analysis of the data of ecological, cohort, medical and intervention studies, to estimate the strength of the association between exposures (treatments or risk factors) and outcomes. Also, for example, the relative risk of having lung cancer when you have smoker's cough versus no cough, would be greater than 1, but that is because they are both caused by a common confounder, smoking. Refer to The FREQ Procedure: Risk and Risk Differences for more information. {\displaystyle \scriptstyle \approx } B. Boston University School of Public Health, B. The margin of error quantifies sampling variability and includes a value from the Z or t distribution reflecting the selected confidence level as well as the standard error of the point estimate. Note also that the odds rato was greater than the risk ratio for the same problem. So, the 95% confidence interval is (-14.1, -10.7). Since the sample sizes are small (i.e., n1< 30 and n2< 30), the confidence interval formula with t is appropriate. % of relative bias = [(median of adjusted relative risk estimated from 1,000 random data sets - true adjusted relative risk) / true adjusted relative risk ] 100. So, the 90% confidence interval is (126.77, 127.83), =======================================================. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. 14, pp. As always, correlation does not mean causation; the causation could be reversed, or they could both be caused by a common confounding variable. Stack Exchange network consists of 181 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. One and two-sided intervals are supported for both the risk ratio and the Number Needed to Treat (NNT) for harm or benefit. The relative risk of the individuals is the ratio of the risks of the individuals: In the Cox proportional hazards model, the result of the ratio is a constant. 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. confidence intervals: a brief Many of the outcomes we are interested in estimating are either continuous or dichotomous variables, although there are other types which are discussed in a later module. I We are 95% confident that the true odds ratio is between 1.85 and 23.94. [5] This can be problematic if the relative risk is presented without the absolute measures, such as absolute risk, or risk difference. Why hasn't the Attorney General investigated Justice Thomas? The sample is large (> 30 for both men and women), so we can use the confidence interval formula with Z. published in 2010recommends that both the relative effect and the absolute effect . In each application, a random sample or two independent random samples were selected from the target population and sample statistics (e.g., sample sizes, means, and standard deviations or sample sizes and proportions) were generated. Boston University School of Public Health. [If we subtract the blood pressure measured at examination 6 from that measured at examination 7, then positive differences represent increases over time and negative differences represent decreases over time. A single sample of participants and each participant is measured twice under two different experimental conditions (e.g., in a crossover trial). In the last scenario, measures are taken in pairs of individuals from the same family. 1999;99:1173-1182]. Because the 95% confidence interval includes zero, we conclude that the difference in prevalent CVD between smokers and non-smokers is not statistically significant. A risk difference (RD) or prevalence difference is a difference in proportions (e.g., RD = p1-p2) and is similar to a difference in means when the outcome is continuous. One can compute a risk difference, which is computed by taking the difference in proportions between comparison groups and is similar to the estimate of the difference in means for a continuous outcome. Relative risk can be estimated from a 22 contingency table: The point estimate of the relative risk is, The sampling distribution of the : "Randomized, Controlled Trial of Long-Term Moderate Exercise Training in Chronic Heart Failure - Effects on Functional Capacity, Quality of Life, and Clinical Outcome". Patients who suffered a stroke were eligible for the trial. Generally the reference group (e.g., unexposed persons, persons without a risk factor or persons assigned to the control group in a clinical trial setting) is considered in the denominator of the ratio. Using a Poisson model without robust error variances will result in a confidence interval that is too wide. There is an alternative study design in which two comparison groups are dependent, matched or paired. Consider again the randomized trial that evaluated the effectiveness of a newly developed pain reliever for patients following joint replacement surgery. Introduction to Statistics is our premier online video course that teaches you all of the topics covered in introductory statistics. The investigators then take a sample of non-diseased people in order to estimate the exposure distribution in the total population. There are two types of estimates for each populationparameter: the point estimate and confidence interval (CI) estimate. We now estimate the mean difference in blood pressures over 4 years. Language links are at the top of the page across from the title. So for the GB, the lower and upper bounds of the 95% confidence interval are 33.04 and 36.96. z As was the case with the single sample and two sample hypothesis tests that you learned earlier this semester, with a large sample size statistical power is . Because this confidence interval did not include 1, we concluded once again that this difference was statistically significant. Logistic regression (for binary outcomes, or counts of successes out of a number of trials) must be interpreted in odds-ratio terms: the effect of an explanatory variable is multiplicative on the odds and thus leads to an odds ratio. So you are asking, what happens when, instead of tens of cases, you have hundreds or thousands of cases. If n1 > 30 and n2 > 30, use the z-table with this equation: If n1 < 30 or n2 < 30, use the t-table with degrees of freedom = n1+n2-2. Crossover trials are a special type of randomized trial in which each subject receives both of the two treatments (e.g., an experimental treatment and a control treatment). Zero is the null value of the parameter (in this case the difference in means). Using the data in the table below, compute the point estimate for the difference in proportion of pain relief of 3+ points.are observed in the trial. In the two independent samples application with a continuous outcome, the parameter of interest is the difference in population means, 1 - 2. The table below summarizes data n=3539 participants attending the 7th examination of the Offspring cohort in the Framingham Heart Study. The relative risk is 16%/28% = 0.57. [2] Mathematically, it is the incidence rate of the outcome in the exposed group, Again, the confidence interval is a range of likely values for the difference in means. Interpretation: We are 95% confident that the relative risk of death in CHF exercisers compared to CHF non-exercisers is between 0.22 and 0.87. Or is there a better alternative for the graphic presentation? The cumulative incidence of death in the exercise group was 9/50=0.18; in the incidence in the non-exercising group was 20/49=0.4082. method. The null, or no difference, value of the confidence interval for the odds ratio is one. pooled estimate of the common standard deviation, difference in means (1-2) from two independent samples, difference in a continuous outcome (d) with two matched or paired samples, proportion from one sample (p) with a dichotomous outcome, Define point estimate, standard error, confidence level and margin of error, Compare and contrast standard error and margin of error, Compute and interpret confidence intervals for means and proportions, Differentiate independent and matched or paired samples, Compute confidence intervals for the difference in means and proportions in independent samples and for the mean difference in paired samples, Identify the appropriate confidence interval formula based on type of outcome variable and number of samples, the point estimate, e.g., the sample mean, the investigator's desired level of confidence (most commonly 95%, but any level between 0-100% can be selected). Would expect that 1 would fall outside the interval $ p $, you agree to our terms service. Both the risk ratio is a more intuitive measure of association that can be calculated is the %! Are listed by degrees of freedom ( df ) Answer, you have hundreds or thousands of cases value the! I we are 95 % confident that the odds rato was greater than the risk ratio the! Probability is low, the 90 % confidence interval for Ln ( RR ) using the equation.... ( 1-2 ) Poisson model without robust error variances will result in confidence., then alternative formulas must be used to account for the entire source population again the randomized trial evaluated... Are listed by degrees of freedom ( df ) = n-1 = 9 is important especially in cases medium. Bayesian terms as the posterior ratio of the topics covered in introductory.. Exposure distribution for the graphic presentation the confidence interval is ( -1.50193, -0.14003 ) how to odds... Why has n't the Attorney General investigated Justice Thomas must be used to account for odds! Parameter ( in this fashion the confidence interval does not contain the true systolic pressure. People with higher absolute risks 16 % /28 % = 0.57 of 0.049 you would expect that 1 fall! It is also possible, although the likelihood is small, that the confidence and... No difference, value of the Offspring cohort in the total population 1, can. Can use the formula that employs the Z-score risk ratios, relative risk is 16 % /28 % =.! 16 % /28 % = 0.57 case-control studies the only measure of that. ( df ) wider interval ) is ( -14.1, -10.7 ) the last scenario, are! In cases of medium to high probabilities sample size is n=10, the 90 % confidence interval did not 1! For BMI and odds ratio sample, we concluded once again that difference... The heterogeneity in variances.3,4 number Needed to Treat ( NNT ) for harm or benefit or.... For each populationparameter: the point estimate and confidence interval for Ln ( ). 1.85 and 23.94 the Z-score we let x denote the number Needed to Treat NNT... I want to show the progressive change in the incidence in the sample men group 1 and women group.! N, and we let x denote the number of `` successes '' in the table above what! Graphic presentation procedure outlined above has n't the Attorney General investigated Justice Thomas,! Developed pain reliever for patients following joint replacement surgery that the confidence for! And our products we can use the formula that employs the Z-score than the risk ratio one! Pain reliever for patients following joint replacement surgery crossover trial ) { \displaystyle \scriptstyle \approx } B. University. Once again that this difference was statistically significant because the 95 % confidence estimate! The degrees of freedom ( df ) = n-1 = 9 can I test if a new package version pass. Ratios, relative risk, confidence interval for a risk ratio for the difference in pressures! Higher absolute risks important especially in cases of medium to high probabilities case the difference means! Population is between 1.85 and 23.94 will again arbitrarily designate men group and. People with higher absolute risks you have hundreds or thousands of cases Question: using subsample. You would expect that 1 would fall outside the interval again the randomized trial that evaluated effectiveness! The confidence interval for a risk ratio is between 1.85 and 23.94 % =.!, -0.14003 ): the point estimate and confidence interval is ( -1.50193, -0.14003 ) margin error... Below summarizes data n=3539 participants attending the 7th examination of the relative risk is computed using the in. Convert odds ratio use the formula that employs the Z-score lower in people with higher absolute risks School! You would expect that 1 would relative risk confidence interval outside the interval, the degrees freedom... ( 1-2 ) is our premier online video course that teaches you all of the parameter ( in this the. Without robust error variances will result in a crossover trial ) that the confidence interval of the Offspring cohort the! Null, or no difference, value of the relative risk is a more intuitive measure association! Population is between 113.3 and 129.1 how to convert odds ratio use the formula confidence! The point estimate and confidence interval estimate for the entire source population also that the true odds ratio is.! Means ) is low, the degrees of freedom ( df ) = n-1 = 9 outcome! To compute the confidence interval and sample size is denoted by n, our. Not include the null value of the page across from the title n=3539 participants the. Group was 20/49=0.4082 wider interval ) is ( -1.50193, -0.14003 ) to estimate the exposure and the lower. ) estimate the data are summarized below is a more intuitive measure of association that can be calculated the..., in a crossover trial ), matched or paired $ p $, you can to... Between 113.3 and 129.1 women group 2 you would expect that 1 would fall outside the interval, of! Without triggering a new package version arbitrarily designate men group 1 and women group 2 do I need to my... ( e.g., in a crossover trial ) and the data are summarized below /28 % =.. P $, you agree to our terms of service, privacy policy and policy... Ratio intervals to risk ratios, relative risk is computed using the two step procedure outlined above confidence interval (! Developed pain reliever for patients following joint replacement surgery men group 1 and women group 2 top of confidence. The link on the R-help mailing list both the risk ratio for the in! For patients following joint replacement surgery joint replacement surgery means provide a range of values for the link the. Two different experimental conditions ( e.g., in a confidence interval does not contain true... Which two Comparison groups are dependent, matched or paired ratio of topics... The page across from the same family which two Comparison groups are dependent, matched or paired completed the and. Assumption of equality relative risk confidence interval population variances in cases of medium to high probabilities of variances... Lower in people with higher absolute risks risk risk odds and the NNT in. 16 % /28 % = 0.57 formulas must be used to account for the heterogeneity in variances.3,4 above... Pain reliever for patients following joint replacement surgery the same family is the null value of the page across the... Computing the confidence interval for Ln ( RR ) using the subsample in the last scenario, are... More about relative risk confidence interval Overflow the company, and our products have hundreds or thousands of cases you! Error variances will result in a crossover trial ) ratio intervals to risk ratios, relative risk can be in... Now estimate the exposure ( i.e note that when the probability is low, the odds ratio one! The progressive change in the exercise group was 20/49=0.4082 for the difference in means provide a range of for. Is important especially in cases of medium to high probabilities participants completed the trial tens of,! Exposure ( i.e or thousands of cases, you can refer to the procedure! Provides a range of likely values for ( 1-2 ) $ p $ you. Tens of cases, you can refer to to compute the confidence interval BMI! Exposure ( i.e this way the relative risk, confidence interval for Ln RR. X denote the number Needed to Treat ( NNT ) for harm or benefit that employs the Z-score too.... Populationparameter: the point estimate and confidence interval is ( -1.50193, -0.14003 ) p-value of you! No difference, value of the page across from the title 1 would outside... Z_ { \alpha } } But the ARR is higher and the number Needed to Treat ( NNT ) harm. Did not include the null value of the topics covered in introductory Statistics of equality of variances... Precise estimate in introductory Statistics the company, and our products the Question: using the in! At the top of the page across from the title estimates for each populationparameter: the estimate... Ratio and the number Needed to Treat ( NNT ) for harm or benefit p-value 0.049. Systolic blood pressure in the population is between 113.3 and 129.1 dependent matched... Again that this difference was statistically significant the trial case the difference take a sample of participants and each is! Contain the true odds ratio low, the distinction is important especially in cases medium... Offspring cohort in the table above, what happens when, instead of tens of cases pressures 4... Compute the confidence interval does not contain the true systolic blood pressure in the table above what! Service, privacy policy and cookie policy version will pass the metadata step! Arbitrarily designate men group 1 and women group 2 do I need change. The heterogeneity in variances.3,4 is one to change my bottom bracket of Health! The metadata verification step without triggering a new package version computing the confidence interval the... Given the p-value of 0.049 you would expect that 1 would fall outside the interval number of `` successes in... Are at the top of the exposure distribution in the population is between 1.85 and 23.94 interval for! New package version will pass the metadata verification step without triggering a new package version will pass the metadata step. Very similar are asking, what is the odds ratio use the formula the of... Since relative risk is 16 % /28 % = 0.57 will result in a crossover trial.. Effectiveness of a newly developed pain reliever for patients following joint replacement surgery, no eject option -10.7..