[R] Ancova_non-normality of errors

From: Tobias Erik Reiners <Tobias.Reiners_at_bio.uni-giessen.de>
Date: Sun, 04 May 2008 11:56:09 +0200


Hello Helpers,

I have some problems with fitting the model for my data...
-->my Literatur says (crawley testbook)=
Non-normality of errors-->I get a banana shape Q-Q plot with opening of banana downwards

Structure of data:

      origin   wt   pes gender
1      wild 5.35 147.0   male
2      wild 5.90 148.0   male
3      wild 6.00 156.0   male
4      wild 7.50 157.0   male
5      wild 5.90 148.0   male
6      wild 5.95 148.0   male
7      wild 8.55 160.5   male
8      wild 5.90 148.0   male
9      wild 8.45 161.0   male
10     wild 4.90 147.0   male
11     wild 6.80 153.0   male
12     wild 5.75 146.0   male
13     wild 8.60 160.0   male
14  captive 6.85 159.0   male

15 captive 7.00 160.0 male
16 captive 6.80 155.0 male
..
...
283    site 4.10 130.4 female
284    site 3.55 131.1 female
285    site 4.20 135.7 female
286    site 3.45 128.0 female
287    site 3.65 125.3 female

The goal of my analysis is to work out what effect the categorial factors(origin, gender) on the relation between log(wt)~log(pes)(-->Condition, fett ressource), have. Does the source(origin) of translocated animals have an affect on performance(condition)in the new area?
I have already a best fit model and it looks quite good (or not?see below).

two slopes(gender difference)and 6 intercepts(3origin levels*2gender levels)

lm(formula = log(wt) ~ log(pes) + origin + gender + gender:log(pes))

Residuals:

      Min 1Q Median 3Q Max
-0.54181 -0.07671 0.01520 0.09474 0.28818

Coefficients:

                     Estimate Std. Error t value Pr(>|t|)
(Intercept)         -7.39879    1.97605  -3.744 0.000219 ***
log(pes)             1.78020    0.40118   4.437 1.31e-05 ***
originsite           0.06572    0.01935   3.397 0.000781 ***
originwild           0.07655    0.03552   2.155 0.032011 *
gendermale          -9.32418    2.37476  -3.926 0.000109 ***
log(pes):gendermale 1.90393 0.47933 3.972 9.06e-05 ***
---

Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.1433 on 281 degrees of freedom Multiple R-Squared: 0.7227, Adjusted R-squared: 0.7177 F-statistic: 146.4 on 5 and 281 DF, p-value: < 2.2e-16

When plot this model I get a banana-shape in Normal Q-Q Plot(with open site pointing downwards) , indicating non-normality of my data....how to handle this?

-->Do I have unbalanced data?

       captive    site    wild
n-->     119     149      19

My problem is that I see that my data is not as good as the modelsummary tells.
Should I include another term in my model formular?

I think I have to differenciate more, but I don't know how.(contrasts?, TukeyHSD?,Akaike Information Criterion? or lme())to many different ways out there.

Cheers,
Tobi



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