UNITED STATES ENVIRONMENTAL PROTECTIONAGENCY WASHINGTON, D.C. 20460



### MEMORANDUM Date: 8/21/14 OFFICE OF CHEMICAL SAFETYAND POLLUTION PREVENTION



### SUBJECT: Metrafenone. Review ofResidue Datafrom Hops Field Trials- Statistical Test for Outlier. PC Code: 000325 Decision No.: 484338 Petition No.: 3E8211 DPBarcode: D421923 Registration No.: 7969-284 Regulatory Action: Section 3 Registration Case No.: NA Assessment Type: Single Chemical Aggregate TXRNo.: NA CAS No.: 220899-03-6 40 CFR: 180.624 MRIDNo.: NA
FROM: 

### Bayazid H. Sarkar, Mathematical Statistician

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# ~~ Chemistry and Exposure Branch 

## U Health Effects Division

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### r· David J. 

### Miller, Chief [ 'tfJ/.· (;·

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### v Chemistry and**Exposur~J3ranch** THROUGH: 

### Health Effects Division (7509P) TO: 

### Dennis McNeilly, Chemist and Risk Assessor Risk Assessment Branch II Health Effects Division (7509P) And Andrew Ertman/Barbara Madden (RM05) Risk Integration, Minor Use, Emergency Response Branch Registration Division (7505P)

Page 

### 1 of8Background HEDIRABII is reviewing a request from the Interregional Research Project No. 4 (IR-4) to establish tolerances for residues ofthe fungicide metrafenone inhops. The data are the subject of ajointreview project with Health Canada's Pest Management Regulatory Agency (PMRA). The submitted hops data included field trials conducted in both North America and in Europe. There are currentlyno establishedtolerances ormaximumresidue limits (MRLs) for metrafenone inhops in the US, Canada or Codex Alimentarius (Codex). The registrant (BASF) and IR4 submitted information pertaining to field trial ON05 (conducted in Ontario), including issues pertaining to adverse weather conditions (hurricane) and excessive insect damage. As a result, BASF and IR4 requested the Agency consider the ON05 residue to exclude it from consideration in establishing the tolerance due to extreme weather conditions resulting in a crop that would not be considered commerciallyviable. RAB IIrequested CEB evaluatethe outlieranalysis submittedbyBASF/IR4, and to determine whether the cited residue value can appropriately be discarded. Conclusion TheHealthEffectsDivision(HED)has reviewedthepetitioner's submissionentitled "Amendment to submission ofthe IR-4 metrafenone (3-bromo-6-methoxy-2-methylphenyl)(2,3,4-trimethoxy6-methylphenyl) methanone study on Hops" submitted on June 27, 2014 by IR4/petitioner supporting the outlierjustification for metrafenone residue data on hops. HED also examined the sensitivity (using several different scenarios) ofthe OECD Calculation Procedures to the ON05 hops trial data. Based on 1) the result ofoutlier test; 2) the sensitivity ofthe tolerance calculation to inclusion ofvarious data sets (e.g. with and without consideration ofthe citedresidue value and EU residue data of dried hops for the same pesticide); and 3) the extreme conditions reported during the ON05 field trial thatresulted ina cropthat was notcommercially viable, HED/CEB has determined that the residue from the ON05 trial can be justifiably excluded from the MRL calculations for hops.
Detailed Considerations Grubbs' Outlier Test In the analysis submitted by the petitioner/IR-4, Grubbs' testwas conducted to determine whether the residue value from ON05 trial is an outlier. The petitioner also demonstrated that the cited residue value from the ON05 trial is greater than the sum ofthe third quartile, and three times the interquartile range. Based on the result of Grubbs' test and the interquartile test, the petitioner concluded thatthe residue value from the ON05 trial is an outlier and should be excluded from the MRL calculation. However,_the petitioner has conducted Grubbs' test without verifying/validating the assumption ofnormality ofthe dried hops residue data. An assumption ofnormality ofthe underlying data is one ofthe criteria that must be met in order to make valid inference from Grubb's test. Ifthe underlying data do not satisfy the normality assumption it is not appropriate to conduct Grubbs' outlier test on data without appropriate transformation. For example, according toe-Handbook of Statistical Method byNational Institute ofStandards and Technology (NIST), Grubbs' test is used
Page 

### 2 of8to detect a single outlier in a univariate dataset that 

### follows an approximate normal distribution. Therefore assumption ofnormality should be tested before conducting Grubbs' test. We note that residue data are not commonly assumed to be sampled from a Normal distribution because residue distribution usually contains a heavy tail and is right skewed which are not characteristics of the Normal distribution. Shapiro-Wilk test for normality or some other appropriate test should be conducted to determine whether the data satisfy the normality assumption. If the data are demonstrated to be non-normal by failing the normality test, the appropriate transformations ofthe data are required to make the data approximately normal prior to conducting Grubb's test. When HED evaluated the hops data for normality, there was sufficient evidence to reject the assumption ofnormality [P value (0.002) for the Shapiro-Wilk test for normality is less than 0.05 for the untransformed residue data. See the appendix for R output] HED then log-transformed the registrant data on hops and the Shapiro-Wilk test failed to reject the normality ofthe transformed data, which is the null hypothesis (p-value of0.07). Hence there is not sufficient evidence to reject the assumption of normality for the transformed data at significance level 0.05. Therefore HED conducted Grubbs' test ontransformed data: Original residue data: 16.8699, 21.89205, 12.71335, 131.92473, 23.52335 Log Transformed data: 2.825531, 3.086124,2.542653,4.882232,3.157994 Mean ofthe log-transformed data: 3.298906 Standard Deviation (SD) ofthe log-transformed data: 0.9176131 Grubbs' test was conducted using log transformed data to test whether 4.882232 which is the log of 131.92473 (the sample from the ON05 field trial) is an outlying observation from the rest of the data: Grubbs'Test statistic = 

# lxm-xl = , 4

.882232

-**29890**

# ~ =1.725483 

### s 0.9176131 Significance level = 0.05 Critical value 1 is 1.715. (See Appendix for calculation ofcritical value using R)

1the formula to derive the critical value is provided in the e-Handbook ofStatistical method by NIST Page 3 of8

### Since the test statistic is greater 

### than the critical value, there is sufficient evidence to reject the null hypothesis and conclude that 4.882232 which is log(131.92473) is in fact outlier at 0.05 level. Although HED reached the same conclusion as the petitioner about the outlying observation of the ON05 trial residue in dried hops, HED believes it is more appropriate to conduct the Grubbs' test using log-transformed data for dried hops (as was done above). Interquartile Range (IQR) Test: 

### HED reviewedthe IQRtest performedbythepetitioner!IR4 and found thatthe cited residue value from the ON05 trial is indeed greater than the sum ofthe third quartile and three times the inter quartilerange (i.e. IQR). Accordingto the NISTe- HandbookofStatistical Method, apointgreater than the sum ofthe third quartile and three times the inter quartile range (i.e. Q3 + 3*IQR) is considered an extreme outlier. However 

### it should be noted that the IQR criterion is not a robust measure ofoutlierwhenthedataarederivedfrom a skewed distribution2•

### Residue dataoftenfollow right skewed distribution (e.g. lognormal). Therefore, the result from IQR test may not be considered as confirmatory by itself. It 

### can be used in conjunction with other tests to decide the outlying observation. Tolerance/MRL Calculation Considerations: Sensitivity ofON05 field trial in Tolerance calculation and comparison with EU data: It

### was notedthatthehighestresidues indried hops cones were observed in samples from the ON05 trial where the second application was delayed due to a hurricane and where, according to the petitioner, halfofthe crop was destroyed by insects between applications3• 

### In addition, HED examined the sensitivity of ON05 hops field trial residue in the tolerance calculation. HED determined that ifthe ON05 trial result is included in the tolerance calculation (using the OECD MRL calculation procedure) then the tolerance value is five times larger than the value calculated excluding the ON05 trial result, i.e., yielding a value of300 ppm including the data, and 60 ppm excluding the data. HED also determined the tolerance value relying only on European data for dried hops, resulting in a tolerance of80 ppm. The MRL calculated using Europeandata is closetothe MRL derived from NAFTA field trial dataexcludingthe sample from the ON05 trial. HED also determined the MRL resulting from use of combined data sets (NAFTA+ EU and excluding ON05 trial), resulting in a value of70 ppm. HED also noted that ifthe ON05 residue is included in the calculation ofthe highest (per trial average) residue value for dried hops, the NAFTA result is much higher than the European result [131.9 ppm (NAFTA) vs. 34.4 ppm EU)]. However the distribution of residue values is approximately comparable ifthe ON05 trial is excluded.

2 Mia Hubert and E. Vandervieren (2004) An adjusted boxplot for skewed distributions. 3 see EPA DER ofMRID No. 49145403 (metrafenone on hops) for details [Drew, D411389, 7/7/14] 

### Page 

### 4 of8Case 1) Calculate the MRL using all data from the NAFTA field trials: NAFTA Field Trial residues= 16.8699,21.89205, 12.71335, 131.92473,23.52335 MRL=300. Case 2) Calculate the MRL using all data from NAFTA field trial except the ON05 trial results: NAFTA Field Trial residues= 16.8699, 21.89205, 12.71335, 23.52335 MRL=60 Case 3) Calculate the MRL using EU dried hops residue data: EU Dried hops residues: 21.3, 22.8, 13.3, 19.7, 34.4, 33.05 MRL=80 Case 4) Calculate the MRL using EU 

### +NAFTA hops data excluding the ON05 trial results: NAFTA 

### +EU residues: 16.8699,21.89205, 12.71335,23.52335,21.3, 22.8, 13.3, 19.7, 34.4, 33.05 MRL=70 [Note: All MRLs were calculated using the OECD MRL calculationprocedures]
Conclusion: Based onthe result ofthe outliertest, combined with consideration ofthe EU data in addition to the various "what if'tolerance calculations and the fact that the ON05 field trial was subject to unusual conditions, HED has concluded that a more reasonable tolerance can be calculated by eliminating the outlier value.
References: Amendment to submission ofthe IR-4 metrafenone (3-bromo-6-methoxy-2-methylphenyl)(2,3,4- trimethoxy-6-methylphenyl) methanone study on Hops" submitted onJune 27, 2014


### NISTISEMATECHe-Handbook of StatisticalMethod, Grubbs' Test for Outliers: http://www.itl.nist.gov/div898/handbook/eda/section3/eda35h1.htm , date: 08/11/2014 

### Mia Hubert andE. 

### Vandervieren (2004) An adjustedboxplotforskeweddistributions. COMPSTAT'2004 Symposium D407432, D411389, D414077, D416465, D417602, William T. Drew: Jul 7, 2014. Metrafenone. Petition to Establish Permanent Tolerances (with Section 3 Registration) for Page 5 of8Residues Resulting from Use ofthe Fungicide on Apricot, Cherry Subgroup 12-12A, Peach Subgroup 12-12B, Fruiting Vegetables Group 8-10, Small Vine Climbing Fruit ExceptFuzzy Kiwifruit Subgroup 13-07F, Hops, Pome Fruits Group 11-10, and Cucurbit Vegetables Group 9; Evaluation ofConditional Data. Summary ofAnalytical Chemistry and Residue Data.


# Appendix #R output for Shapiro-WilkNormality test:



### > # Untransformed residue data 

### > y 

## =c(16.8699, 21.89205, 12.71335, 131.92473, 23.52335) 

### > > shapiro.test (y) Shapiro-Wilk normality test
data: y W 

## =0.6333, p-value

## =0.001673



### > #log-transformed residue data 

### > > z 

## =c(2.825531, 3.086124,2.542653,4.882232, 3.157994) 

### > > > shapiro.test (z) Shapiro-Wilk normality test

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### 6 of8data: z W = 0.7939, p-value = 0.07222

# R code for Grubbs' test critical value calculation : Grubbs<- function( N, alpha){

g =alpha 

### I (2*N)

a=qt(g, df=N-2)

b = ((N-1)/sqrt(N)) * sqrt(a"2/(N-2 +a"2))

return (b) } 

### > y1 = Grubbs(5, 0.05) >y1 [1] 1.715037

##### IQR Criterion#### 

### > quantile (y) 0% 25% 50% 75% 100% 12.71335 16.86990 21.89205 23.52335 131.92473



### > IQR(y) Page 7 of8[1] 6.65345 

### > 3*IQR(y) [1] 19.96035 

### > 23.52335 

### + 3*IQR(y) [I] 43.4837



### Page 8 of8