Description Usage Format Source Examples
Blood clotting activity (PCA) is measured for 158 Norway rats from two locations just before (baseline) and four days after injection of an anticoagulant (bromadiolone). Normally this would cause reduced blood clotting after 4 days compared to the baseline, but these rats are known to possess anticoagulent resistence to varying extent. The purpose is to relate anticoagulent resistence to gender and location and perhaps weight. Dose of injection is, however, admistered according to weight and gender.
1 |
A data frame with 158 observations on the following 6 variables.
rat
a numeric vector
locality
a factor with levels Loc1
Loc2
sex
a factor with levels F
M
weight
a numeric vector
PCA0
a numeric vector with percent blood clotting activity at baseline
PCA4
a numeric vector with percent blood clotting activity on day 4
Ann-Charlotte Heiberg, project at
The Royal Veterinary and Agricultural University, 1999.
Added by Ib M. Skovgaard <ims@life.ku.dk>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | data(clotting)
dim(clotting)
head(clotting)
day0= transform(clotting, day=0, pca=PCA0)
day4= transform(clotting, day=4, pca=PCA4)
day.both= rbind(day0,day4)
m1= lm(pca ~ rat + day*locality + day*sex, data=day.both)
anova(m1)
summary(m1)
m2= lm(pca ~ rat + day, data=day.both)
anova(m2)
## Log transformation suggested.
## Random effect of rat.
## maybe str(clotting) ; plot(clotting) ...
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[1] 158 6
rat locality sex weight PCA0 PCA4
1 1 Loc1 F 284 78.6 73.2
2 2 Loc1 F 274 65.2 67.8
3 3 Loc1 F 276 78.2 91.9
4 4 Loc1 F 298 62.9 76.3
5 5 Loc1 F 284 55.3 53.1
6 6 Loc1 F 266 77.7 80.1
Analysis of Variance Table
Response: pca
Df Sum Sq Mean Sq F value Pr(>F)
rat 1 3090 3090 1.5599 0.21263
day 1 12083 12083 6.0996 0.01406 *
locality 1 86364 86364 43.5985 1.757e-10 ***
sex 1 679 679 0.3430 0.55852
day:locality 1 309 309 0.1561 0.69301
day:sex 1 5339 5339 2.6953 0.10166
Residuals 309 612094 1981
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
lm(formula = pca ~ rat + day * locality + day * sex, data = day.both)
Residuals:
Min 1Q Median 3Q Max
-102.075 -25.065 -5.473 12.944 307.721
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 78.2248 7.5826 10.316 < 2e-16 ***
rat 0.4522 0.2120 2.133 0.03371 *
day -0.8559 2.0795 -0.412 0.68093
localityLoc2 -55.9472 18.0586 -3.098 0.00213 **
sexM 14.0545 11.0268 1.275 0.20342
day:localityLoc2 -0.9210 2.5049 -0.368 0.71337
day:sexM -4.1593 2.5335 -1.642 0.10166
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 44.51 on 309 degrees of freedom
Multiple R-squared: 0.1498, Adjusted R-squared: 0.1333
F-statistic: 9.075 on 6 and 309 DF, p-value: 3.78e-09
Analysis of Variance Table
Response: pca
Df Sum Sq Mean Sq F value Pr(>F)
rat 1 3090 3089.9 1.3723 0.24232
day 1 12083 12082.6 5.3660 0.02118 *
Residuals 313 704786 2251.7
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
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