Back to the Top
Dear All,
I Thanks in advance, if anyone could clarify my
question. In the Statistical Analysis of one study, We came acrose
this situation.
The Anova for LnAUCt as Dependent variable, and Sequence, Period , Sub
(seq) and Treatment as independent variables carried out.
the results are as follows:
R-Square Coeff Var Root MSE lnAUCt
Mean
0.853861 4.139193 0.199158
4.811522
Source DF Type III SS Mean
Square F Value Pr > F
seq 1 0.00000001
0.00000001 0.00 0.9997
sub(seq) 30 6.95082384
0.23169413 5.84 <.0001
per 1 0.00039561
0.00039561 0.01 0.9211
trt 1 0.00131702
0.00131702 0.03 0.8566
Tests of Hypotheses Using the Type III MS for sub(seq)
as an Error Term
Source DF Type III SS Mean
Square F Value Pr > F
seq 1 5.3387176E-9
5.3387176E-9 0.00 0.9999
as observed in the above result, the type III S.S and M.S.S for Seq is
5.3387176E-9 and Probability is 0.9999
Could any one tell me, whether this result is acceptable.
What could be the interpretation?
explain it.
Back to the Top
The following message was posted to: PharmPK
Where statistics have failed it does not mean automatically that the
results are bad. Have you tried other statistical tests besides
ANOVA??? You do have several choices
s.o.o
Back to the Top
The following message was posted to: PharmPK
For bioequivalence studies, the ANOVA sequence effect must be tested
against Subject nested within Sequence (Subj(Seq)). Therefore, and
according to your results, p value for sequence effect is 0.9999, which
means that your study sequence effect is not statistically significative
(p<0.05).
Best regards
Nuno Silva
Faculty of Pharmacy, U.L.
Biopharmaceutics and Pharmacokinetics Dept.
Av. Prof. Gama Pinto
1649 003 Lisbon / Portugal
Tel: (+351) 217 946 406
Fax: (+351) 217 937 703
E-mail: nmens.-at-.ff.ul.pt
Back to the Top
The following message was posted to: PharmPK
Dear Shekar
There's an important piece of information missing in your posting
pertaining to the pooled variance for the error term in your analysis
of variance. Without a full picture it's hard to tell you whether
your conclusions, rather than your results, are acceptable.
You may be aware of an unfortunate misconception that still lingers
around about the use of p-value. Many people still believe that it
indicates the strength or the magnitude of a given comparison, when
in fact it doesn't. A p-value of 0.00001 does not imply that the
magnitude of the difference between lets say treatments is larger
than when the p-value is 0.049. For example, a p-value of 0.6
relative to the F ratio for the formulations does not provide any
information about bioequivalence if the mean square error is let's
say 0.4. Likewise, a p-value of 0.0000005 for the formulations
doesn't convey any information about bioequivalence if the p-value
for the sequence (carryover) effect is let's say 0.001. Testing
separately the carryover effect will allow the use of the proper
corrected p-value and adequate bioequivalence testing.
So I suggest that you put all the pieces of the puzzle together and
be ware for the misleading p-value.
A short but significant communication by Brian P. Smith, "It's time"
The AAPS Journal 2005, 7(3), E655, may lead you in the way.
Cheers
Luis
--
Luis M. Pereira, Ph.D.
Assistant Professor, Biopharmaceutics and Pharmacokinetics
Massachusetts College of Pharmacy and Health Sciences
179 Longwood Ave, Boston, MA 02115
Phone: (617) 732-2905
Fax: (617) 732-2228
Luis.Pereira.aaa.bos.mcphs.edu
Back to the Top
Hi,
I think the problem is that your model is overfitted. The treatment
is uniquely determined by the combination of sequence and period if
the design is a crossover design. But you included sequence, period
and treatment all in the predictors. Notice that the F-value for the
sequence is close to zero which comfirmed this. Hope this can help you!
Best Regards,
Gerry Li
Back to the Top
Hi,
I think the problem is that your model is overfitted. The treatment
is uniquely determined by the combination of sequence and period if
the design is a crossover design. But you included sequence, period
and treatment all in the predictors. Notice that the F-value for the
sequence is close to zero which comfirmed this. Hope this can help you!
Best Regards,
Gerry
Back to the Top
The following message was posted to: PharmPK
----Would anynone out there consider it prudent to proceed with an
ANOVA without verifying the suitability of the data beforehand.
Back to the Top
The following message was posted to: PharmPK
Does verification mean the distribution of data?
In my opinion, the repeated ANOVA is based on the CI, which already
taking into account of the error in Mean.
Nadeem
Back to the Top
The following message was posted to: PharmPK
----That is obvious, indeed the credibility of anova test is gained
thru verifying the dependent and the factor elements. For instance:
The Mean Square Error (MSE) of an estimate is the variance of the
estimate plus the square of its bias; therefore, if an estimate is
unbiased, then its MSE is equal to its variance, as it is the case in
the ANOVA table.
--
Jamil Finsi
Back to the Top
The following message was posted to: PharmPK
There're several assumptions need to be checked before drawing the
conclusions.
PharmPK Discussion List Archive Index page
Copyright 1995-2010 David W. A. Bourne (david@boomer.org)