From: Manibusan, Mary

To: Matten, Sharlene

Subject: Fw: Answers to the clarification questions from the SAP (Tier 2)

Date: Wednesday, June 26, 2013 2:40:25 PM

Mary Manibusan, Director 

(202) 564-2827

From: Flynn, Kevin

Sent: Wednesday, June 26, 2013 2:37:36 PM

To: Manibusan, Mary

Subject: Answers to the clarification questions from the SAP (Tier 2)

The responses to the clarification questions from the SAP from the

statistician involved in both the MMT/MRT and LAGDA data analysis are below.

I believe his responses answer the questions from the SAP. For further

clarity and context, the LAGDA data was indeed analyzed as understood by the

SAP. Therefore, the response below is mostly germane to the MMT. As a point

of clarification, the SAS code was not altered in the re-analysis, rather the

data from the LAGDA was properly formated to reflect weighted replicate means

that were then inputted into StatCHARRMS. On the other hand, the MMT data

was inputted directly into a separate module of StatCHARRMS named somewhat

confusingly "Repeated Measures" (see Response to question 2A below) and the

StatCHARRMS program analyzed the data as described below.

This afternoon, Drs. Mary Christman and Dallas Johnson, asked EPA to clarify the 1-way

ANOVA and the repeated measures 2-way ANOVAs as used in the Medaka

multigeneration test (MMT) and Larval amphibian growth and development assay

(LAGDA).

1) In the 1-way ANOVA corrected code, does the correction for MMT:

a) Use the mean value for all individuals in a tank and the weights proportional to

sample size as was done to calculate the mean for the tank in the LAGDA? Or

b) Use individual observations as the experimental units and add a random effect for

the tank within treatment and include denominator degrees of freedom adjusted

according to the Kenward-Roger (KR) (or Satterthwaite) method? or

c) Something else?

Response for question 1

 The repeated measures ANOVA module within StatCharms is designed to run
specific macros depending on the nature of the data. In particular if time (and generation)

only has one level within the data set a mixed effects procedure (proc mixed) is ran with

fixed effects for the model defaulting to the treatment and the random effects defaulting

to replicate within treatment. This is how the analysis in the errata for the MMT was

performed.

2) In the repeated measures ANOVA for MMT, the fixed effects are treatment and

time, BUT that alone does not account for the repeated observations on the same

experimental unit.

a) How were repeated observations handled? That is what is the covariance

among the error terms?

Response for question 2 A:

 Repeated measures ANOVA in StatChaRRms is a misnomer. The program actual uses

mixed effect models to performs the analysis. 

 If time has multiple levels within the data set the program still uses the uses mixed

procedure but uses Time, Treatment and the Time-Treatment interaction as fixed

effects. The random effects are replicate within the time-treatment interaction and are

'grouped' (using the SAS group option) by Time.

b) How were repeated observations handled if a non-parametric ANOVA was

performed because of lack of normality?

Response for question 2 B:

 If the residuals are found to be non-normal the program rank transforms each

observation (within a generation for each generation) by rank using the rank procedure with

the blom option and using the (transformed) mean when ties occur. The program then

proceeds as normal on the transformed data.

3) If the residuals show normality, but unequal variances among treatments, was a usual

ANOVA and KR method or a nonparametric ANOVA done?

For question 3:

 This depends on the module. The module used for LAGDA will use a TamhaneDunnett test for post hoc comparisons, when the residuals are normal but there is unequal

variances amongst treatments. The module used for the MMT treats a failure to pass the

Levenes test like a failure to pass the Shapiro Wilks test. This means if both tests cannot be

satisfied by a transformation the module will rank transform the data and proceed as

described in the paragraph above for response 2 B.

Kevin Flynn

USEPA/ORD/NHEERL/MED

218-529-5120