. Suppose we are interested in the sensitivity/speci city of PSA (greater than 2ng/ml) in predicting relapse within 24 months. 14 answers. It has been recommended that the measures of statistical uncertainty should be reported, such as the 95% confidence interval, when evaluating the accuracy of diagnostic examinations. The sensitivity and specificity are probabilities, so confidence intervals can be calculated for them using standard methods for proportions. To learn more, see our tips on writing great answers. The reference test is scores and the other test is f145. * Estimate the confidence interval naively.. di 0.44 - invnorm(0.975) * .07019972, 0.44 + invnorm(0.975) * .07019972 . Likelihood Ratio = sensitivity/(1 specificity) The likelihood ratio indicates the value of the test for increasing certainty about a positive diagnosis. Usually as most data is normal. The sensitivity and specificity do not give us this information. Using Stata for Confidence Intervals - Page 1 . For example, if you had a study of 100 people and 50 were able to complete your task, then the 95% confidence interval will be 20% wide (from 40% to 60%), but the 80% confidence interval will be only 12% wide (from 44% to 56%). Answer will appear in the blue cells. Construct a 95% c.i. If the same test was used in a different clinical setting where the prevalence of abnormality was 0.25 we would have an estimated positive predictive value of 0.45 and an estimated negative predictive value of 0.95. Develop the tech skills you need for work and life. What method is used here to calculate confidence intervals? Using Stata: ( cii is confidence interval immediate ) . The accuracy (overall diagnostic accuracy) is defined as: Accuracy = Sensitivity * Prevalence + Specificity * (1 - Prevalence) Using the F-distribution, the CP CI interval is given as: But I am not sure what to substitute for: x: # of . Producing confidence intervals for sensitivity and specificity in SAS, Different confidence interval between R and SPSS results, Confidence interval for partial correlations, Analyzing data in SPSS using ROC Curve For categorical variables (nominal). Thanks to all authors for creating a page that has been read 122,033 times. The post-test odds of disease given a positive test is 0.878/(1 -0.878) = 7.22, and the likelihood ratio is 0.895/(1 - 0.628) = 2.41. Why don't we know exactly where the Chinese rocket will fall? cii 258 231 -- Binomial Exact -- Variable | Obs Mean Std. All methods assume that data are obtained by binomial sampling, with the number of true positives and true negatives in the study fixed by design. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Comparing the difference in sensitivity or specificity of a novel examination with the reference standard is important when evaluating its usefulness. 2022 Moderator Election Q&A Question Collection. Are there small citation mistakes in published papers and how serious are they? 2 # c. a ^s. for eg sensitivity= true negative/ (true negative+ false positive)! The Likelihood Ratio Negative (LR-) is 0.3663 and the 95% C.I. The 95% confidence interval for the true population mean weight of turtles is [292.36, 307.64]. Setting Up and the corresponding 100(1-\)% confidence interval, c) The Positive Predictive Value and the corresponding 100(1-\)% confidence interval, d) The Negative Predictive Value and the corresponding 100(1-\)% confidence interval, e) The Pre-test probability, Positive Post-test probability, Negative Post-test probability, f) The Likelihood Ratio Positive, Likelihood Ratio Negative and their corresponding 100(1-\)% confidence interval. A higher confidence level leads to a wider confidence interval than that corresponding to a lower confidence level. Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. Leave one out sensitivity analysis for single arm meta analysis. In terms of a meta-analysis, sensitivity means that you get all of what you want. The difference between the prior and posterior probabilities is one way of assessing the usefulness of the test. In statistics, a binomial proportion confidence interval is a confidence interval for the probability of success calculated from the outcome of a series of success-failure experiments (Bernoulli trials).In other words, a binomial proportion confidence interval is an interval estimate of a success probability p when only the number of experiments n and the number of successes n S are known. rev2022.11.4.43007. interval was, say, (0.45 - 0.55) we'd argue that the parameter uncertainty less than if it were (0.2 - 0.70) All that is parameter uncertainty This article has been viewed 122,033 times. Sensitivity = a/ (a+c) Specificity = d/ (b+d) +ve predictive value = a/ (a+b) -ve predictive value = d/ (d+c) Likelihood ratio of a positive test = [a/ (a+c)]/ [b/ (b+d)] Sensitivity is an intrinsic test parameter independent of disease prevalence; the confidence level of a tests sensitivity, however, depends on the sample size. The program will calculate the 95% confidence intervals for 50 samples, each with a mean of 50 and a standard deviation of 10. Asked 6th Feb, 2018; Komathi Perumal; First step, make an Excel file. Thus in screening the general population it is inevitable that many people with positive test results will be false positives. I am using SPSS for producing ROC curve, but ROC cure does not give me the confidence-interval for sensitivity and specificity. In your example, the following gives a confidence interval around the optimal X cutoff when you replace "youden-prob-level" with the predicted probability associated with your Youden-optimal cutpoint. diagti 231 27 32 54,prev(50) True | disease | Test result status | Pos. Why so many wires in my old light fixture? I will try the continuous biomarker measurements for curiosity but I susupect that my colleagues will want to use the binary measures for practical purposes. This is generally given for a specific test as part of the tests intrinsic characteristic. Generalizing the 95% Confidence Interval Critical value, z /2 is a multiplier for a (1-) 100% For 95% CI, = 0.5, so the Z-value of the standard normal is at 0.025, that is z = 1.96 For any probability value (1- ) there is a number z /2 such that any normal distribution has probability (1- ) within z /2 standard deviations of the mean. Confidence intervals for the between study variance are useful in random-effects meta-analyses because they quantify the uncertainty in the corresponding point estimates. For any test result we can compare the probability of getting that result if the patient truly had the condition of interest with the corresponding probability if he or she were healthy. How can we build a space probe's computer to survive centuries of interstellar travel? The Positive Predictive Value (PPV) is 0.1 and the 95% C.I. Entering .proportion varlist can produce estimates of proportions, standard errors, and CIs for the categories identified by the values in each variable of varlist. We use cookies to make wikiHow great. Yes, dichotomania. Conf interval - Likelihood ratio. Positive predictive value is the probability that a patient with abnormal test results is truly abnormal. Sensitivity = Probability ( T+ | D+ ) The specificity of a test is the probability that the test is negative given a patient does not have the condition. Binomial parameter p. Problem. Confidence intervals are examples of interval estimates. 95% Confidence Interval to Bar Graph. small samples or for proportions close to 0 or 1. Read 5 answers by scientists to the question asked by Yi Su on Jul 10, 2016 is (5.54896, 9.88828). { a p v L ! For example, the table shows the relation between the results of a test, a liver scan, and the correct diagnosis based on either necropsy, biopsy, or surgical inspection. Similarly, among the 81 patients with normal liver scans the proportion of correct diagnoses was 54/81 = 0.59. I am using the following code to calculate exact confidence intervals for sensitivity and specificity. The objective of a sensitivity analysis is to understand 1) which are the most important inputs/parameters that a ect our study/model and 2) quantify the overall uncertainty of our models . It is assumed that t 1, t 2, , t k are independent and identically distributed as N ( 0, 2) random variables. Interval] -------------+--------------------------------------------------------------- | 86 .627907 .0521224 .5169596 .7297749 Sensitivity and specificity are one approach to quantifying the diagnostic ability of the test. wikiHow is a wiki, similar to Wikipedia, which means that many of our articles are co-written by multiple authors. wikiHow is a wiki, similar to Wikipedia, which means that many of our articles are co-written by multiple authors. There's no further need for an independent samples t-test on these data. Relation between results of liver scan and correct diagnosis ----------------------------------------------------------- Pathology --------------------------------------------- Abnormal Normal Liver scan (+) (-) Total ----------------------------------------------------------- Abnormal(+) 231 32 263 Normal(-) 27 54 81 ----------------------------------------------------------- Total 258 86 344 One approach is to calculate the proportions of patients with normal and abnormal liver scans who are correctly "diagnosed" by the scan. Find centralized, trusted content and collaborate around the technologies you use most. So if anyone can help me to produce confidence-interval for Sensitivity and specificity in SPSS will be the biggest help for me. B. ! Making statements based on opinion; back them up with references or personal experience. The gaps in between the lines are the absent rows 3,6, 9, and 12. I split my time between clinical work and research and so I am conflicted on this issue. Specificity (with optional 95% Confidence Interval): Probability that a test result will be negative when the disease is not present (true negative rate). N = 100, p^ = .40. A 90% confidence interval for the difference between independent means runs from -2.3 to 6.4. When the migration is complete, you will access your Teams at stackoverflowteams.com, and they will no longer appear in the left sidebar on stackoverflow.com. Specificity means that you get none of what you don't want. Spanish - How to write lm instead of lim? Solution. I am using STATA 14 for the analysis. using diagti 37 6 8 28 goes well except for the 95%ci's of sensitivity and specificity the paper gives 95%ci's as sp = 78% (65 to 91%) sn = 86% (75 to 97%) have you any idea how these may have been calculated - tried all cii options also the prevalence is This example shows how to draw the confidence interval, but not how to calcultate them. Not the answer you're looking for? Then the Sensitivity is 0.66667 and the corresponding 95% C.I. Asking for help, clarification, or responding to other answers. Interval] -------------+--------------------------------------------------------------- | 258 .8953488 .0190572 .8513977 .9298934 . ((1-\) =0.95) is (0.49798, 0.83535). Neyman [ 76] proposed the construction of confidence intervals in this way because they have the following property: If one calculates, say, 95 % confidence intervals repeatedly in valid applications, 95 % of them, on average, will contain (i.e., include or cover) the true effect size. To determine the 95% confidence interval, follow these steps. It is a difficult problem because on the one hand you lose a lot of information by dichotomizing a variable but on the other, at some point you have to define what is and is not an abnormal test result in order to have any usefulness clinically. Keywords: In this section we'll discuss two commands that estimate the mean value of a variable for a population and give you a 95% confidence interval for that estimate. The ratio of these probabilities is called the likelihood ratio, calculated as sensitivity/ (1 - specificity). The Negative Predictive Value (NPV) is 0.99454 and the 95% C.I. 90% condence interval for rate from a sample with 4,379 deaths over 11,394 person-years cii means 11394 4379, poisson level(90) Agresti-Coull condence interval for proportion based on a sample with 2,377 observations and 136 Confidence Intervals Case II. I usually do both and put at least one in the appendix. Consider that you have several groups, and a set of numerical values for each group. To create this article, volunteer authors worked to edit and improve it over time. Question. Copyright 2011-2019 StataCorp LLC. Sensitivity is the ability of the test to pick up what it is testing for and Specificity is ability to reject what it is not testing for. Moreover, it states "note: 1.l_drought#1.l_excl identifies no observations in the sample" - which I am not sure how to interpret. For the various presented above, several methods of calculating their variance and, therefore their confidence intervals, have been proposed. There are two families: the first concerns proportions, such as sensitivity and specificity, and the second ratios, such as LR+, LR- the odds . The predictive values of a test in clinical practice depend critically on the prevalence of the abnormality in the patients being tested; this may well differ from the prevalence in a published study assessing the usefulness of the test. A barplot can be used to represent the average value of each group. The equation for the Normal Approximation for the Binomial CI is shown below. A confidence interval is the mean of your estimate plus and minus the variation in that estimate. In the code below both l_drought and l_excl are dummy variables. In practice, this distinction is obscured by the fact that most of the time the sample mean is the best estimate for the population mean. Sensitivity (with optional 95% Confidence Interval): Probability that a test result will be positive when the disease is present (true positive rate). Tests performed on small sample sizes (e.g. Moreover, the dependent variable attacks is a dummy variable. where p = proportion of interest; n = sample size; = desired confidence; z 1- /2 = "z value" for desired level of confidence; z 1- /2 = 1.96 for 95% confidence; z 1- /2 = 2.57 for 99% confidence % of people told us that this article helped them. Procedure: Enter a) Value of Disease and No Disease in the Positive and Negative Test Outcome group b) Value of 1-, the two-sided confidence level Click the button "Calculate" to obtain a) The Sensitivity and the corresponding 100 (1-)% confidence interval b) The Specificity and the corresponding 100 (1-)% confidence interval Note: This interval is only exact when the population distribution is . Include your email address to get a message when this question is answered. 2. S^t . The positive and negative predictive values are the revised values of the same probability for those subjects who are positive and negative on the test, and are known as posterior probabilities. Instead we must approach the data from the direction of the test results, using predictive values. Thanks for contributing an answer to Stack Overflow! Example 2: Confidence Interval for a Difference in Means. Once again, thank you Joseph. Follow asked Jun 4, 2016 at 18:07. ramin ramin. Using the invariance property of the MLE allows us to exponentiate to get $$ e^{\beta_j \pm z^* SE(\beta_j)}$$ which is a confidence interval on the odds ratio. from Confidence Interval(CI)? We proposed that the basis for estimation of a screening study is that its sensitivity must be pre-determined to be at least 50.0% within the null hypothesis to indicate that the probability or chance for an instrument to detect a true-positive is in balance with at least 50.0%. cii 258 231 -- Binomial Exact -- Variable | Obs Mean Std. However, excel doesn't recognize these as CIs since they were not calculated in excel (and . By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Wilson Score with CC (0.93168, 0.99943) Notes on C.I. Thus there are 258 true positives and 86 true negatives. : : Z > @F` : Sensitivity, Specificity and Predictive Value [adapted from Altman and Bland BMJ.com] The simplest diagnostic test is one where the results of an investigation, such as an x ray examination or biopsy, are used to classify patients into two groups according to the presence or absence of a symptom or sign. So if anyone can help me to produce confidence-interval for Sensitivity and specificity in SPSS will be the biggest help for me. Discover how to use Stata to calculate a confidence interval for binomial summary data. In other words, what is the probability that a patient with abnormal test results is truly abnormal? And the results without confidence intervals are: Sensitivity: 93.7%. Methods for calculating these confidence intervals have been developed that are based on inverting hypothesis tests using generalised heterogeneity statistics. . Using Stata: ( cii is confidence interval immediate ) . As far as i know, you use the proportion CI calculator in stata, but what values do you put in? : 1) CC means continuity correction. ''NA'' or ''inf'' is reported where the horizontal line does not intersect a confidence interval. You are not logged in. 20-30 samples) have wider confidence intervals, signifying greater imprecision. The sensitivity and specificity are probabilities, so confidence intervals can be calculated for them using standard methods for proportions. Err. Sensitivity is the ability of the test to pick up what it is testing for and specificity is the ability of the test to reject what it is not testing for. Accuracy: 79.7%. is (0.89746, 0.92254). Confidence Intervals for One-Sample Sensitivity and Specificity Usage Note 24170: Sensitivity, specificity, positive and negative predictive values, and other 2x2 table statistics There are many common statistics defined for 22 tables. How to calculate 95% confidence interval for AUC from confusion matrix? Unfortunately, in the resulting regression table, the interaction variable is omitted. For the liver scan data the prevalence of abnormal pathology was estimated to be 0.75, so the pre-test odds of disease was estimated as 0.75/(1 -0.75) = 3.0. However, this kind of figure must be accompanied by error bars showing the confidence interval of each group. . The researcher would like to try AUC values 0.6, 0.7, 0.8, and 0.9. t : 1 S^t 0:50. It is equal to the percentage of positives among all tested persons with the disease or characteristic of interest. My data has 3 columns : ID, true value, billing value If you just have the summary statistics, cii 100 40, level(95) wilson The parameters are the sample size N, the # of successes, the desired confidence . Which gives a confidence interval on the log-odds ratio. Connect and share knowledge within a single location that is structured and easy to search. The posttest odds of having the disease is the pre-test odds multiplied by the likelihood ratio. ci means income. Likelihood ratios determine how the test result changes the probability of certain outcomes and events. Normal Approximation Method of the Binomial Confidence Interval. . To determine the 95% confidence interval, follow these steps. I used the tab command and col option to get the sensitivity and specificity but I will need the CI also. The whole point of a diagnostic test is to use it to make a diagnosis, so we need to know the probability that the test will give the correct diagnosis. Request a different confidence level with option level (#), with # being replaced by, say, 90, 99, or . I have the following data and would like to calculate the confidence interval for the sensitivity and specificity. Confidence intervals for sensitivity, specificity are computed for completeness. Note that all command that follow permit varlists, that is, you can request confidence intervals (of the same type) for several variables. Specificity = Probability ( T- | D- ) We can thus say that, based on the sample studied, we would estimate that 90% of patients with abnormal pathology would have abnormal (positive) liver scans, while 63% of those with normal pathology would have normal (negative) liver scans. . The confidence level is set to 0.95. Posttest odds of disease = (Pretest odds of disease) X (Likelihood Ratio) PV+/(1-PV+) = (Likelihood Ratio) x (prevalence)/(1 prevalence) A high likelihood ratio may show that the test is useful, but it does not necessarily follow that a positive test is a good indicator of the presence of disease. And how serious are they and the 95 % confidence interval, follow these steps positive Predictive (... Numerical values for each group so confidence interval sensitivity stata wires in my old light fixture 0.1 and the 95 confidence! Help for me are there small citation mistakes in published papers and how serious are they need for and... Old light fixture is called the likelihood ratio indicates the value of each group do put... Rss feed, copy confidence interval sensitivity stata paste this URL into your RSS reader all! Showing the confidence interval for AUC from confusion matrix with the disease or characteristic of.! Methods for proportions the appendix must approach the data from the direction of the test 86 true negatives methods... Interval on the log-odds ratio answers by scientists to the percentage of positives among all tested persons with reference. Probe 's computer to survive centuries of interstellar travel are they making based. Your estimate plus and minus the variation in that estimate on this issue from -2.3 to 6.4 option to a... And research and so i am using the following code to calculate the interval... ; s no further need for an independent samples t-test on these data true.. Standard is important when evaluating its usefulness is 0.99454 and the 95 %.... This is generally given for a specific test as part of the test =0.95 ) 0.1! Determine how the test Jun 4, 2016 is ( 5.54896, 9.88828 ) interval for between. The tab command and col option to get a message when this question is.! Specificity of a meta-analysis, sensitivity means that you get all of what you want all! Methods of calculating their variance and, therefore their confidence intervals for sensitivity and specificity do give... Result changes the probability of certain outcomes and events data and would like to try AUC 0.6... Calculate 95 % C.I Notes on C.I the difference between the prior and posterior probabilities is called the likelihood.... At 18:07. ramin ramin a space probe 's computer to survive centuries of interstellar travel to this RSS feed copy. Are interested in the corresponding point estimates ; t recognize these as CIs they... Been developed that are based on inverting hypothesis tests using generalised heterogeneity statistics probability that a with... Of calculating their variance and, therefore their confidence intervals using the following code to calculate confidence intervals can used! Been read 122,033 times 258 true positives and 86 true negatives is answered i have the following data would... Auc values 0.6, 0.7, 0.8, and a set of numerical values for each group 9.88828 ) data. Centralized, trusted content and collaborate around the technologies you use most are interested in the corresponding %... Use the proportion of correct diagnoses was 54/81 = 0.59 the resulting regression table the! All of what you want standard is important when evaluating its usefulness in terms a... Of each group why do n't we know exactly where the Chinese rocket will fall the results confidence... A single location that is structured and easy to search curve, but what values do put! Jun 4, 2016 is ( 0.49798, 0.83535 ) to get the and... By scientists to the percentage of positives among all tested persons with the reference test is f145 address! Build a space probe 's computer to survive centuries of interstellar travel confidence interval sensitivity stata negatives. Of correct diagnoses was 54/81 = 0.59 determine the 95 % confidence interval the., trusted content and collaborate around the technologies you use most 5 answers by scientists the! One in the sensitivity/speci city of PSA ( greater than 2ng/ml ) in predicting relapse within 24 months:. Specificity of a meta-analysis, sensitivity means that you get all of what you want the CI.. Stata, but what values do you put in their confidence intervals know, you use the proportion correct! False positives edit and improve it over time is 0.1 and the 95 % C.I the %. Used here to calculate the confidence interval of each group the Chinese rocket will fall moreover, the dependent attacks... Methods of calculating their variance and, therefore their confidence intervals for sensitivity and specificity was 54/81 =.! Logo 2022 Stack Exchange Inc ; user contributions licensed under CC BY-SA must be accompanied by error bars the. Between clinical work and life their variance and, therefore their confidence intervals, have been developed that are on. Corresponding point estimates creating a page that has been read 122,033 times 0.49798, 0.83535 ) what the... For calculating these confidence intervals, have been developed that are based opinion. T-Test on these data confidence interval sensitivity stata variable | Obs Mean Std 1-\ ) =0.95 ) is 0.99454 and the %... Absent rows 3,6, 9, and 12 between clinical work and life odds having. Error bars showing the confidence interval of each group of these probabilities is called likelihood. ( NPV ) is 0.1 and the 95 % C.I specificity ) try values. A lower confidence level small samples or for proportions wilson Score with CC ( 0.93168, 0.99943 ) on! To the question asked by Yi Su on Jul 10, 2016 is 5.54896! 9, and 12 to produce confidence-interval for sensitivity and specificity do not give us this.., among the 81 patients with normal liver scans the proportion CI calculator in Stata, but values. Your email address to get a message when this question is answered, as. Spss for producing ROC curve, but ROC cure does not give me the confidence-interval for sensitivity and specificity computed. Of certain outcomes and events inevitable that many people with positive test is. Determine how the test results is truly abnormal for completeness specificity are probabilities so... Be false positives work and life no further need for work and research and so i using. 4, 2016 at 18:07. ramin ramin exactly where the Chinese rocket will fall see our tips on writing answers... Suppose we are interested in the corresponding point estimates was 54/81 =.! About a positive diagnosis probabilities is called the likelihood ratio indicates the value of the test, or to... Predictive value ( PPV ) is 0.3663 and the other test is f145 is answered C.I... Having the disease is the probability that a patient with abnormal test results is truly abnormal over time the odds! Prev ( 50 ) true | disease | test result changes the probability that a with. Interaction variable is omitted disease is the pre-test odds multiplied by the likelihood ratio indicates the value of each.... ( LR- ) is 0.99454 and the results without confidence intervals, signifying greater imprecision the probability that patient! Excel doesn & # x27 ; t recognize these as CIs since they were not calculated in excel (.... Likelihood ratios determine how the test for increasing certainty about a positive.. Single location that is structured and easy to search a wiki, similar to Wikipedia, means... No further need for an independent samples t-test on these data from confusion matrix the prior and probabilities! Reference standard is important when evaluating its usefulness variance are useful in random-effects meta-analyses because quantify! Exact confidence intervals have been proposed in my old light fixture interaction variable is omitted like to calculate confidence! Calculated for them using standard methods for proportions close to 0 or 1 Feb, ;... Know, you use most try AUC values 0.6, 0.7, 0.8, and 0.9. t: S^t. Been proposed you have several groups, and a set of numerical values for group. Summary data positive Predictive value ( PPV ) is 0.3663 and the results without confidence,. For completeness called the likelihood ratio Negative ( LR- ) is ( 0.49798, 0.83535 ) generalised heterogeneity statistics the... What you don & # x27 ; t want numerical values for each.! Exact confidence intervals can be calculated for them using standard methods for calculating these intervals... Contributions licensed under CC BY-SA these data message when this question is answered code both. About a positive diagnosis 5 answers by scientists to the percentage of positives among tested. Are they a higher confidence level leads to a lower confidence level to! Odds multiplied by the likelihood ratio, calculated as sensitivity/ ( 1 - specificity ) is shown below --. Inc ; user contributions licensed under CC BY-SA of PSA ( greater than 2ng/ml ) in relapse! Not calculated in excel ( and old light fixture from confusion matrix for producing ROC,. Interval is the probability that a patient with abnormal test results is truly abnormal part of the.. Yi Su on Jul 10, 2016 at 18:07. ramin ramin ( true negative+ false positive ) article volunteer... And easy to search of assessing the usefulness of the test result status |.... Using Predictive values AUC values 0.6, 0.7, 0.8, and 0.9. t 1. Between clinical work and research and so i am conflicted on this issue me the confidence-interval sensitivity! Exchange Inc ; user contributions licensed under CC BY-SA command and col option get! In that estimate to calculate a confidence interval is the pre-test odds multiplied by likelihood. The technologies you use most are based on inverting hypothesis tests using generalised heterogeneity statistics this.. Sensitivity= true negative/ ( true negative+ false positive ) figure must be accompanied by error bars showing the confidence for... Groups, and 0.9. t: 1 S^t 0:50 easy to search all what... Spss will be the biggest help for me excel file weight of turtles [! Doesn & # x27 ; t want split my time between clinical work and and. Feb, 2018 ; Komathi Perumal ; First step, make an excel.. What values do you put in the difference between independent means runs from to...
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