batchtest: Performs test to check whether batch needs to be adjusted
In BatchQC: Batch Effects Quality Control Software
Description
Usage
Arguments
Value
Examples
Description
Performs test to check whether batch needs to be adjusted
Usage
1
Arguments
pca
PCA object from principal component analysis
batch
Batch covariate
mod
Model matrix for outcome of interest and other covariates
besides batch
Value
Summary of linear regression of first five principal components
Examples
1
2
3
4
5
6
7
8
9
10
11
12
nbatch <- 3
ncond <- 2
npercond <- 10
data.matrix <- rnaseq_sim(ngenes=50, nbatch=nbatch, ncond=ncond, npercond=
npercond, basemean=10000, ggstep=50, bbstep=2000, ccstep=800,
basedisp=100, bdispstep=-10, swvar=1000, seed=1234)
batch <- rep(1:nbatch, each=ncond*npercond)
condition <- rep(rep(1:ncond, each=npercond), nbatch)
pdata <- data.frame(batch, condition)
modmatrix = model.matrix(~as.factor(condition), data=pdata)
pca <- batchqc_pca(data.matrix, batch, mod=modmatrix)
batchtest(pca, batch, mod=modmatrix)
Example output
sh: 1: cannot create /dev/null: Permission denied
Call:
lm(formula = pc[, 1] ~ fbatch + fcond)
Residuals:
Min 1Q Median 3Q Max
-1.95358 -0.45328 0.04717 0.60252 1.57878
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -7.4258 0.2051 -36.20 <2e-16 ***
fbatch2 5.9121 0.2512 23.53 <2e-16 ***
fbatch3 12.5239 0.2512 49.85 <2e-16 ***
fcond1 2.5608 0.2051 12.48 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.7945 on 56 degrees of freedom
Multiple R-squared: 0.9793, Adjusted R-squared: 0.9781
F-statistic: 881.1 on 3 and 56 DF, p-value: < 2.2e-16
Call:
lm(formula = pc[, 2] ~ fbatch + fcond)
Residuals:
Min 1Q Median 3Q Max
-3.7975 -0.6522 0.1296 0.7709 2.8918
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.09594 0.32455 0.296 0.769
fbatch2 -0.43845 0.39749 -1.103 0.275
fbatch3 -0.07704 0.39749 -0.194 0.847
fcond1 0.15179 0.32455 0.468 0.642
Residual standard error: 1.257 on 56 degrees of freedom
Multiple R-squared: 0.02788, Adjusted R-squared: -0.0242
F-statistic: 0.5354 on 3 and 56 DF, p-value: 0.66
Call:
lm(formula = pc[, 3] ~ fbatch + fcond)
Residuals:
Min 1Q Median 3Q Max
-4.6201 -0.6683 0.2035 0.6785 2.6077
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.339994 0.300463 1.132 0.26264
fbatch2 -0.001188 0.367990 -0.003 0.99744
fbatch3 0.195881 0.367990 0.532 0.59663
fcond1 -0.809783 0.300463 -2.695 0.00927 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.164 on 56 degrees of freedom
Multiple R-squared: 0.1201, Adjusted R-squared: 0.07296
F-statistic: 2.548 on 3 and 56 DF, p-value: 0.06497
Call:
lm(formula = pc[, 4] ~ fbatch + fcond)
Residuals:
Min 1Q Median 3Q Max
-3.3476 -0.7101 -0.0702 0.6425 2.4201
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.23142 0.29813 -0.776 0.441
fbatch2 0.39746 0.36513 1.089 0.281
fbatch3 -0.04282 0.36513 -0.117 0.907
fcond1 0.22641 0.29813 0.759 0.451
Residual standard error: 1.155 on 56 degrees of freedom
Multiple R-squared: 0.04019, Adjusted R-squared: -0.01122
F-statistic: 0.7817 on 3 and 56 DF, p-value: 0.5091
Call:
lm(formula = pc[, 5] ~ fbatch + fcond)
Residuals:
Min 1Q Median 3Q Max
-2.6261 -0.7063 0.0244 0.7560 2.1307
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.1117 0.2764 -0.404 0.6877
fbatch2 -0.2357 0.3385 -0.696 0.4891
fbatch3 -0.1891 0.3385 -0.559 0.5787
fcond1 0.5066 0.2764 1.833 0.0721 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.071 on 56 degrees of freedom
Multiple R-squared: 0.06516, Adjusted R-squared: 0.01508
F-statistic: 1.301 on 3 and 56 DF, p-value: 0.2831
$call
lm(formula = pc[, 1] ~ fbatch + fcond)
$terms
pc[, 1] ~ fbatch + fcond
attr(,"variables")
list(pc[, 1], fbatch, fcond)
attr(,"factors")
fbatch fcond
pc[, 1] 0 0
fbatch 1 0
fcond 0 1
attr(,"term.labels")
[1] "fbatch" "fcond"
attr(,"order")
[1] 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: 0xc9f6db0>
attr(,"predvars")
list(pc[, 1], fbatch, fcond)
attr(,"dataClasses")
pc[, 1] fbatch fcond
"numeric" "factor" "factor"
$residuals
1 2 3 4 5 6
-0.46611041 1.46286517 0.67356663 -0.68252775 0.49949592 0.74902441
7 8 9 10 11 12
-0.11415040 -0.86476060 0.68476961 -1.49574840 0.09938608 -0.53631554
13 14 15 16 17 18
1.07727822 0.74014899 0.40514804 -1.95357677 -0.08305834 -0.26219989
19 20 21 22 23 24
-0.06197237 0.12873740 0.65964268 -1.00522026 0.01055691 0.76287893
25 26 27 28 29 30
-0.14575829 -1.47343195 0.28664538 0.66568565 -0.65497228 0.62023860
31 32 33 34 35 36
-1.62106060 -0.01952931 0.99270340 0.96844451 0.54498337 0.50736683
37 38 39 40 41 42
0.80330660 -0.88376258 -0.73049157 -0.28822603 -0.08420487 0.59661773
43 44 45 46 47 48
-1.33830464 -0.23245537 1.57877806 -0.35295223 0.18691956 0.18093849
49 50 51 52 53 54
-1.24190125 0.53387496 -0.13204140 -0.44899714 0.08377980 0.12073816
55 56 57 58 59 60
0.22584524 0.11480677 1.15658040 -0.78632546 -0.14081949 -0.02087732
$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) -7.425752 0.2051310 -36.20004 1.539484e-40
fbatch2 5.912143 0.2512332 23.53250 1.024518e-30
fbatch3 12.523882 0.2512332 49.84964 4.362911e-48
fcond1 2.560820 0.2051310 12.48382 8.139951e-18
$aliased
(Intercept) fbatch2 fbatch3 fcond1
FALSE FALSE FALSE FALSE
$sigma
[1] 0.794469
$df
[1] 4 56 4
$r.squared
[1] 0.9792548
$adj.r.squared
[1] 0.9781434
$fstatistic
value numdf dendf
881.1391 3.0000 56.0000
$cov.unscaled
(Intercept) fbatch2 fbatch3 fcond1
(Intercept) 0.06666667 -5.000000e-02 -5.000000e-02 -3.333333e-02
fbatch2 -0.05000000 1.000000e-01 5.000000e-02 -1.839961e-17
fbatch3 -0.05000000 5.000000e-02 1.000000e-01 -2.340556e-18
fcond1 -0.03333333 -1.839961e-17 -2.340556e-18 6.666667e-02
$call
lm(formula = pc[, 2] ~ fbatch + fcond)
$terms
pc[, 2] ~ fbatch + fcond
attr(,"variables")
list(pc[, 2], fbatch, fcond)
attr(,"factors")
fbatch fcond
pc[, 2] 0 0
fbatch 1 0
fcond 0 1
attr(,"term.labels")
[1] "fbatch" "fcond"
attr(,"order")
[1] 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: 0xc9f6db0>
attr(,"predvars")
list(pc[, 2], fbatch, fcond)
attr(,"dataClasses")
pc[, 2] fbatch fcond
"numeric" "factor" "factor"
$residuals
1 2 3 4 5 6
0.25600500 -0.03149638 0.16359255 0.31912197 0.55984699 -0.18818923
7 8 9 10 11 12
-0.66429953 0.11333571 -0.37880905 -0.42137161 -0.50986627 0.14578110
13 14 15 16 17 18
0.60536084 0.44250432 -0.48242725 0.75210718 -0.27693196 -1.61027691
19 20 21 22 23 24
0.37875385 0.82725867 -1.51001513 -0.69489384 0.70340786 -0.12810957
25 26 27 28 29 30
1.49674025 -1.18130200 0.71864130 0.94102885 0.70208638 1.38197236
31 32 33 34 35 36
0.01953037 0.57337199 1.20934423 -0.28704994 -0.21400315 -1.70144047
37 38 39 40 41 42
1.08290858 -0.83347830 -2.04221325 -0.23652654 2.89179506 0.16237839
43 44 45 46 47 48
1.09916500 -3.07558237 0.99330608 0.99194686 -0.64813251 -1.99219213
49 50 51 52 53 54
-1.03513496 -1.54484232 1.08135056 1.14286460 -3.79746153 0.63468113
55 56 57 58 59 60
1.47413782 -0.70030060 -0.56106648 2.87317569 1.22777780 -1.21786609
$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.09593908 0.3245487 0.2956076 0.7686231
fbatch2 -0.43845211 0.3974894 -1.1030536 0.2747216
fbatch3 -0.07704423 0.3974894 -0.1938271 0.8470126
fcond1 0.15178606 0.3245487 0.4676834 0.6418260
$aliased
(Intercept) fbatch2 fbatch3 fcond1
FALSE FALSE FALSE FALSE
$sigma
[1] 1.256972
$df
[1] 4 56 4
$r.squared
[1] 0.02787995
$adj.r.squared
[1] -0.02419791
$fstatistic
value numdf dendf
0.5353513 3.0000000 56.0000000
$cov.unscaled
(Intercept) fbatch2 fbatch3 fcond1
(Intercept) 0.06666667 -5.000000e-02 -5.000000e-02 -3.333333e-02
fbatch2 -0.05000000 1.000000e-01 5.000000e-02 -1.839961e-17
fbatch3 -0.05000000 5.000000e-02 1.000000e-01 -2.340556e-18
fcond1 -0.03333333 -1.839961e-17 -2.340556e-18 6.666667e-02
$call
lm(formula = pc[, 3] ~ fbatch + fcond)
$terms
pc[, 3] ~ fbatch + fcond
attr(,"variables")
list(pc[, 3], fbatch, fcond)
attr(,"factors")
fbatch fcond
pc[, 3] 0 0
fbatch 1 0
fcond 0 1
attr(,"term.labels")
[1] "fbatch" "fcond"
attr(,"order")
[1] 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: 0xc9f6db0>
attr(,"predvars")
list(pc[, 3], fbatch, fcond)
attr(,"dataClasses")
pc[, 3] fbatch fcond
"numeric" "factor" "factor"
$residuals
1 2 3 4 5 6
-0.44357285 0.88992339 -0.57990996 -0.04843986 0.71755940 0.33817658
7 8 9 10 11 12
-0.38106237 -0.04340122 0.51568401 -0.99389985 -1.46927952 1.43498822
13 14 15 16 17 18
-1.13285232 0.63746842 0.69661303 0.57321329 -0.16715480 -1.62610896
19 20 21 22 23 24
0.36297915 0.71907622 0.60290407 0.68475597 -0.62732925 0.53964994
25 26 27 28 29 30
-0.86408918 -1.59458001 -1.32694101 0.54812598 0.14990826 -0.73846372
31 32 33 34 35 36
1.15995818 0.67636665 -0.64495913 0.25707765 1.10756558 1.22211427
37 38 39 40 41 42
1.52007633 -0.82870883 -0.55468788 -1.28874388 0.45453102 0.32447239
43 44 45 46 47 48
0.45209051 -0.78499175 -0.31170871 1.54319504 -1.04846568 1.26978399
49 50 51 52 53 54
0.05706515 0.69902972 -1.96836404 2.60765918 -0.45791154 -4.62005933
55 56 57 58 59 60
0.13981892 -0.22262021 2.11774453 -1.04916069 0.47004936 0.32784214
$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.339994025 0.3004628 1.131567626 0.262638759
fbatch2 -0.001187559 0.3679903 -0.003227148 0.997436582
fbatch3 0.195880602 0.3679903 0.532298240 0.596625204
fcond1 -0.809783411 0.3004628 -2.695119990 0.009272101
$aliased
(Intercept) fbatch2 fbatch3 fcond1
FALSE FALSE FALSE FALSE
$sigma
[1] 1.163688
$df
[1] 4 56 4
$r.squared
[1] 0.1201023
$adj.r.squared
[1] 0.07296496
$fstatistic
value numdf dendf
2.547922 3.000000 56.000000
$cov.unscaled
(Intercept) fbatch2 fbatch3 fcond1
(Intercept) 0.06666667 -5.000000e-02 -5.000000e-02 -3.333333e-02
fbatch2 -0.05000000 1.000000e-01 5.000000e-02 -1.839961e-17
fbatch3 -0.05000000 5.000000e-02 1.000000e-01 -2.340556e-18
fcond1 -0.03333333 -1.839961e-17 -2.340556e-18 6.666667e-02
$call
lm(formula = pc[, 4] ~ fbatch + fcond)
$terms
pc[, 4] ~ fbatch + fcond
attr(,"variables")
list(pc[, 4], fbatch, fcond)
attr(,"factors")
fbatch fcond
pc[, 4] 0 0
fbatch 1 0
fcond 0 1
attr(,"term.labels")
[1] "fbatch" "fcond"
attr(,"order")
[1] 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: 0xc9f6db0>
attr(,"predvars")
list(pc[, 4], fbatch, fcond)
attr(,"dataClasses")
pc[, 4] fbatch fcond
"numeric" "factor" "factor"
$residuals
1 2 3 4 5 6
0.676033505 -0.658514298 1.179868113 -1.348393011 1.084563521 0.300738531
7 8 9 10 11 12
0.668547557 0.216140642 0.393492853 -0.356310152 -0.890955549 0.326366538
13 14 15 16 17 18
-0.290742637 -0.461343788 -0.006339403 0.283584088 -0.074497013 -0.438834197
19 20 21 22 23 24
0.599458914 -1.202864213 -0.886205122 0.295894184 1.169700492 -0.738251555
25 26 27 28 29 30
-1.377811845 -0.366983495 -1.283439404 -1.675269985 2.420075700 0.628267220
31 32 33 34 35 36
1.891149748 -0.475023583 0.369056676 -0.247296906 1.210210293 -1.406922987
37 38 39 40 41 42
-0.065842208 -1.123081231 2.060155170 -0.398381163 2.242488550 -0.758852498
43 44 45 46 47 48
-2.196476291 0.582209698 -0.753442289 0.756160747 0.493200050 -0.051397329
49 50 51 52 53 54
-0.559375155 -0.096658933 0.633778589 -3.347550286 -0.255192299 -0.700765984
55 56 57 58 59 60
1.821463075 -1.513095237 1.783774212 -0.491581306 1.305559403 1.105753283
$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.23141955 0.2981283 -0.7762415 0.4408727
fbatch2 0.39745613 0.3651311 1.0885300 0.2810238
fbatch3 -0.04281864 0.3651311 -0.1172692 0.9070663
fcond1 0.22641411 0.2981283 0.7594520 0.4507674
$aliased
(Intercept) fbatch2 fbatch3 fcond1
FALSE FALSE FALSE FALSE
$sigma
[1] 1.154646
$df
[1] 4 56 4
$r.squared
[1] 0.04019473
$adj.r.squared
[1] -0.01122341
$fstatistic
value numdf dendf
0.7817227 3.0000000 56.0000000
$cov.unscaled
(Intercept) fbatch2 fbatch3 fcond1
(Intercept) 0.06666667 -5.000000e-02 -5.000000e-02 -3.333333e-02
fbatch2 -0.05000000 1.000000e-01 5.000000e-02 -1.839961e-17
fbatch3 -0.05000000 5.000000e-02 1.000000e-01 -2.340556e-18
fcond1 -0.03333333 -1.839961e-17 -2.340556e-18 6.666667e-02
$call
lm(formula = pc[, 5] ~ fbatch + fcond)
$terms
pc[, 5] ~ fbatch + fcond
attr(,"variables")
list(pc[, 5], fbatch, fcond)
attr(,"factors")
fbatch fcond
pc[, 5] 0 0
fbatch 1 0
fcond 0 1
attr(,"term.labels")
[1] "fbatch" "fcond"
attr(,"order")
[1] 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: 0xc9f6db0>
attr(,"predvars")
list(pc[, 5], fbatch, fcond)
attr(,"dataClasses")
pc[, 5] fbatch fcond
"numeric" "factor" "factor"
$residuals
1 2 3 4 5 6
0.014654976 0.401223602 -0.404768253 1.091163931 0.215576187 1.069462223
7 8 9 10 11 12
-0.524442392 -0.457715317 0.316172519 0.028050858 -0.131363704 0.729068532
13 14 15 16 17 18
0.876444362 -0.773886975 -0.141427915 -1.611025195 -0.494940481 -0.006850571
19 20 21 22 23 24
0.020746241 -0.216142628 0.139564997 0.481066220 -0.903036108 1.743453156
25 26 27 28 29 30
-1.770321060 0.574808747 -0.320004549 0.836753682 0.052290436 -1.241243657
31 32 33 34 35 36
0.938143151 1.201496731 -0.412531447 -1.129584621 1.016750635 -1.367896424
37 38 39 40 41 42
0.109952917 1.422038943 -0.467118016 -0.904583734 -0.683746034 -1.687276819
43 44 45 46 47 48
1.032950098 -0.217697901 2.087959173 0.531984465 0.566096582 0.662533269
49 50 51 52 53 54
-1.324637126 -2.310875905 -2.626112274 -0.866543417 1.569150540 0.141658302
55 56 57 58 59 60
2.130727900 0.495851644 0.997323696 1.350007810 -1.051296342 -0.798057659
$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.1116920 0.2764076 -0.4040842 0.68768991
fbatch2 -0.2357319 0.3385288 -0.6963422 0.48909486
fbatch3 -0.1890961 0.3385288 -0.5585818 0.57867393
fcond1 0.5066025 0.2764076 1.8328095 0.07214897
$aliased
(Intercept) fbatch2 fbatch3 fcond1
FALSE FALSE FALSE FALSE
$sigma
[1] 1.070522
$df
[1] 4 56 4
$r.squared
[1] 0.0651571
$adj.r.squared
[1] 0.01507623
$fstatistic
value numdf dendf
1.301038 3.000000 56.000000
$cov.unscaled
(Intercept) fbatch2 fbatch3 fcond1
(Intercept) 0.06666667 -5.000000e-02 -5.000000e-02 -3.333333e-02
fbatch2 -0.05000000 1.000000e-01 5.000000e-02 -1.839961e-17
fbatch3 -0.05000000 5.000000e-02 1.000000e-01 -2.340556e-18
fcond1 -0.03333333 -1.839961e-17 -2.340556e-18 6.666667e-02
BatchQC documentation built on Nov. 8, 2020, 8:30 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value Examples
Description
Performs test to check whether batch needs to be adjusted
Usage
1 |
Arguments
pca |
PCA object from principal component analysis |
batch |
Batch covariate |
mod |
Model matrix for outcome of interest and other covariates besides batch |
Value
Summary of linear regression of first five principal components
Examples
1 2 3 4 5 6 7 8 9 10 11 12 | nbatch <- 3
ncond <- 2
npercond <- 10
data.matrix <- rnaseq_sim(ngenes=50, nbatch=nbatch, ncond=ncond, npercond=
npercond, basemean=10000, ggstep=50, bbstep=2000, ccstep=800,
basedisp=100, bdispstep=-10, swvar=1000, seed=1234)
batch <- rep(1:nbatch, each=ncond*npercond)
condition <- rep(rep(1:ncond, each=npercond), nbatch)
pdata <- data.frame(batch, condition)
modmatrix = model.matrix(~as.factor(condition), data=pdata)
pca <- batchqc_pca(data.matrix, batch, mod=modmatrix)
batchtest(pca, batch, mod=modmatrix)
|
Example output
sh: 1: cannot create /dev/null: Permission denied
Call:
lm(formula = pc[, 1] ~ fbatch + fcond)
Residuals:
Min 1Q Median 3Q Max
-1.95358 -0.45328 0.04717 0.60252 1.57878
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -7.4258 0.2051 -36.20 <2e-16 ***
fbatch2 5.9121 0.2512 23.53 <2e-16 ***
fbatch3 12.5239 0.2512 49.85 <2e-16 ***
fcond1 2.5608 0.2051 12.48 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.7945 on 56 degrees of freedom
Multiple R-squared: 0.9793, Adjusted R-squared: 0.9781
F-statistic: 881.1 on 3 and 56 DF, p-value: < 2.2e-16
Call:
lm(formula = pc[, 2] ~ fbatch + fcond)
Residuals:
Min 1Q Median 3Q Max
-3.7975 -0.6522 0.1296 0.7709 2.8918
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.09594 0.32455 0.296 0.769
fbatch2 -0.43845 0.39749 -1.103 0.275
fbatch3 -0.07704 0.39749 -0.194 0.847
fcond1 0.15179 0.32455 0.468 0.642
Residual standard error: 1.257 on 56 degrees of freedom
Multiple R-squared: 0.02788, Adjusted R-squared: -0.0242
F-statistic: 0.5354 on 3 and 56 DF, p-value: 0.66
Call:
lm(formula = pc[, 3] ~ fbatch + fcond)
Residuals:
Min 1Q Median 3Q Max
-4.6201 -0.6683 0.2035 0.6785 2.6077
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.339994 0.300463 1.132 0.26264
fbatch2 -0.001188 0.367990 -0.003 0.99744
fbatch3 0.195881 0.367990 0.532 0.59663
fcond1 -0.809783 0.300463 -2.695 0.00927 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.164 on 56 degrees of freedom
Multiple R-squared: 0.1201, Adjusted R-squared: 0.07296
F-statistic: 2.548 on 3 and 56 DF, p-value: 0.06497
Call:
lm(formula = pc[, 4] ~ fbatch + fcond)
Residuals:
Min 1Q Median 3Q Max
-3.3476 -0.7101 -0.0702 0.6425 2.4201
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.23142 0.29813 -0.776 0.441
fbatch2 0.39746 0.36513 1.089 0.281
fbatch3 -0.04282 0.36513 -0.117 0.907
fcond1 0.22641 0.29813 0.759 0.451
Residual standard error: 1.155 on 56 degrees of freedom
Multiple R-squared: 0.04019, Adjusted R-squared: -0.01122
F-statistic: 0.7817 on 3 and 56 DF, p-value: 0.5091
Call:
lm(formula = pc[, 5] ~ fbatch + fcond)
Residuals:
Min 1Q Median 3Q Max
-2.6261 -0.7063 0.0244 0.7560 2.1307
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.1117 0.2764 -0.404 0.6877
fbatch2 -0.2357 0.3385 -0.696 0.4891
fbatch3 -0.1891 0.3385 -0.559 0.5787
fcond1 0.5066 0.2764 1.833 0.0721 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.071 on 56 degrees of freedom
Multiple R-squared: 0.06516, Adjusted R-squared: 0.01508
F-statistic: 1.301 on 3 and 56 DF, p-value: 0.2831
$call
lm(formula = pc[, 1] ~ fbatch + fcond)
$terms
pc[, 1] ~ fbatch + fcond
attr(,"variables")
list(pc[, 1], fbatch, fcond)
attr(,"factors")
fbatch fcond
pc[, 1] 0 0
fbatch 1 0
fcond 0 1
attr(,"term.labels")
[1] "fbatch" "fcond"
attr(,"order")
[1] 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: 0xc9f6db0>
attr(,"predvars")
list(pc[, 1], fbatch, fcond)
attr(,"dataClasses")
pc[, 1] fbatch fcond
"numeric" "factor" "factor"
$residuals
1 2 3 4 5 6
-0.46611041 1.46286517 0.67356663 -0.68252775 0.49949592 0.74902441
7 8 9 10 11 12
-0.11415040 -0.86476060 0.68476961 -1.49574840 0.09938608 -0.53631554
13 14 15 16 17 18
1.07727822 0.74014899 0.40514804 -1.95357677 -0.08305834 -0.26219989
19 20 21 22 23 24
-0.06197237 0.12873740 0.65964268 -1.00522026 0.01055691 0.76287893
25 26 27 28 29 30
-0.14575829 -1.47343195 0.28664538 0.66568565 -0.65497228 0.62023860
31 32 33 34 35 36
-1.62106060 -0.01952931 0.99270340 0.96844451 0.54498337 0.50736683
37 38 39 40 41 42
0.80330660 -0.88376258 -0.73049157 -0.28822603 -0.08420487 0.59661773
43 44 45 46 47 48
-1.33830464 -0.23245537 1.57877806 -0.35295223 0.18691956 0.18093849
49 50 51 52 53 54
-1.24190125 0.53387496 -0.13204140 -0.44899714 0.08377980 0.12073816
55 56 57 58 59 60
0.22584524 0.11480677 1.15658040 -0.78632546 -0.14081949 -0.02087732
$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) -7.425752 0.2051310 -36.20004 1.539484e-40
fbatch2 5.912143 0.2512332 23.53250 1.024518e-30
fbatch3 12.523882 0.2512332 49.84964 4.362911e-48
fcond1 2.560820 0.2051310 12.48382 8.139951e-18
$aliased
(Intercept) fbatch2 fbatch3 fcond1
FALSE FALSE FALSE FALSE
$sigma
[1] 0.794469
$df
[1] 4 56 4
$r.squared
[1] 0.9792548
$adj.r.squared
[1] 0.9781434
$fstatistic
value numdf dendf
881.1391 3.0000 56.0000
$cov.unscaled
(Intercept) fbatch2 fbatch3 fcond1
(Intercept) 0.06666667 -5.000000e-02 -5.000000e-02 -3.333333e-02
fbatch2 -0.05000000 1.000000e-01 5.000000e-02 -1.839961e-17
fbatch3 -0.05000000 5.000000e-02 1.000000e-01 -2.340556e-18
fcond1 -0.03333333 -1.839961e-17 -2.340556e-18 6.666667e-02
$call
lm(formula = pc[, 2] ~ fbatch + fcond)
$terms
pc[, 2] ~ fbatch + fcond
attr(,"variables")
list(pc[, 2], fbatch, fcond)
attr(,"factors")
fbatch fcond
pc[, 2] 0 0
fbatch 1 0
fcond 0 1
attr(,"term.labels")
[1] "fbatch" "fcond"
attr(,"order")
[1] 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: 0xc9f6db0>
attr(,"predvars")
list(pc[, 2], fbatch, fcond)
attr(,"dataClasses")
pc[, 2] fbatch fcond
"numeric" "factor" "factor"
$residuals
1 2 3 4 5 6
0.25600500 -0.03149638 0.16359255 0.31912197 0.55984699 -0.18818923
7 8 9 10 11 12
-0.66429953 0.11333571 -0.37880905 -0.42137161 -0.50986627 0.14578110
13 14 15 16 17 18
0.60536084 0.44250432 -0.48242725 0.75210718 -0.27693196 -1.61027691
19 20 21 22 23 24
0.37875385 0.82725867 -1.51001513 -0.69489384 0.70340786 -0.12810957
25 26 27 28 29 30
1.49674025 -1.18130200 0.71864130 0.94102885 0.70208638 1.38197236
31 32 33 34 35 36
0.01953037 0.57337199 1.20934423 -0.28704994 -0.21400315 -1.70144047
37 38 39 40 41 42
1.08290858 -0.83347830 -2.04221325 -0.23652654 2.89179506 0.16237839
43 44 45 46 47 48
1.09916500 -3.07558237 0.99330608 0.99194686 -0.64813251 -1.99219213
49 50 51 52 53 54
-1.03513496 -1.54484232 1.08135056 1.14286460 -3.79746153 0.63468113
55 56 57 58 59 60
1.47413782 -0.70030060 -0.56106648 2.87317569 1.22777780 -1.21786609
$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.09593908 0.3245487 0.2956076 0.7686231
fbatch2 -0.43845211 0.3974894 -1.1030536 0.2747216
fbatch3 -0.07704423 0.3974894 -0.1938271 0.8470126
fcond1 0.15178606 0.3245487 0.4676834 0.6418260
$aliased
(Intercept) fbatch2 fbatch3 fcond1
FALSE FALSE FALSE FALSE
$sigma
[1] 1.256972
$df
[1] 4 56 4
$r.squared
[1] 0.02787995
$adj.r.squared
[1] -0.02419791
$fstatistic
value numdf dendf
0.5353513 3.0000000 56.0000000
$cov.unscaled
(Intercept) fbatch2 fbatch3 fcond1
(Intercept) 0.06666667 -5.000000e-02 -5.000000e-02 -3.333333e-02
fbatch2 -0.05000000 1.000000e-01 5.000000e-02 -1.839961e-17
fbatch3 -0.05000000 5.000000e-02 1.000000e-01 -2.340556e-18
fcond1 -0.03333333 -1.839961e-17 -2.340556e-18 6.666667e-02
$call
lm(formula = pc[, 3] ~ fbatch + fcond)
$terms
pc[, 3] ~ fbatch + fcond
attr(,"variables")
list(pc[, 3], fbatch, fcond)
attr(,"factors")
fbatch fcond
pc[, 3] 0 0
fbatch 1 0
fcond 0 1
attr(,"term.labels")
[1] "fbatch" "fcond"
attr(,"order")
[1] 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: 0xc9f6db0>
attr(,"predvars")
list(pc[, 3], fbatch, fcond)
attr(,"dataClasses")
pc[, 3] fbatch fcond
"numeric" "factor" "factor"
$residuals
1 2 3 4 5 6
-0.44357285 0.88992339 -0.57990996 -0.04843986 0.71755940 0.33817658
7 8 9 10 11 12
-0.38106237 -0.04340122 0.51568401 -0.99389985 -1.46927952 1.43498822
13 14 15 16 17 18
-1.13285232 0.63746842 0.69661303 0.57321329 -0.16715480 -1.62610896
19 20 21 22 23 24
0.36297915 0.71907622 0.60290407 0.68475597 -0.62732925 0.53964994
25 26 27 28 29 30
-0.86408918 -1.59458001 -1.32694101 0.54812598 0.14990826 -0.73846372
31 32 33 34 35 36
1.15995818 0.67636665 -0.64495913 0.25707765 1.10756558 1.22211427
37 38 39 40 41 42
1.52007633 -0.82870883 -0.55468788 -1.28874388 0.45453102 0.32447239
43 44 45 46 47 48
0.45209051 -0.78499175 -0.31170871 1.54319504 -1.04846568 1.26978399
49 50 51 52 53 54
0.05706515 0.69902972 -1.96836404 2.60765918 -0.45791154 -4.62005933
55 56 57 58 59 60
0.13981892 -0.22262021 2.11774453 -1.04916069 0.47004936 0.32784214
$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.339994025 0.3004628 1.131567626 0.262638759
fbatch2 -0.001187559 0.3679903 -0.003227148 0.997436582
fbatch3 0.195880602 0.3679903 0.532298240 0.596625204
fcond1 -0.809783411 0.3004628 -2.695119990 0.009272101
$aliased
(Intercept) fbatch2 fbatch3 fcond1
FALSE FALSE FALSE FALSE
$sigma
[1] 1.163688
$df
[1] 4 56 4
$r.squared
[1] 0.1201023
$adj.r.squared
[1] 0.07296496
$fstatistic
value numdf dendf
2.547922 3.000000 56.000000
$cov.unscaled
(Intercept) fbatch2 fbatch3 fcond1
(Intercept) 0.06666667 -5.000000e-02 -5.000000e-02 -3.333333e-02
fbatch2 -0.05000000 1.000000e-01 5.000000e-02 -1.839961e-17
fbatch3 -0.05000000 5.000000e-02 1.000000e-01 -2.340556e-18
fcond1 -0.03333333 -1.839961e-17 -2.340556e-18 6.666667e-02
$call
lm(formula = pc[, 4] ~ fbatch + fcond)
$terms
pc[, 4] ~ fbatch + fcond
attr(,"variables")
list(pc[, 4], fbatch, fcond)
attr(,"factors")
fbatch fcond
pc[, 4] 0 0
fbatch 1 0
fcond 0 1
attr(,"term.labels")
[1] "fbatch" "fcond"
attr(,"order")
[1] 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: 0xc9f6db0>
attr(,"predvars")
list(pc[, 4], fbatch, fcond)
attr(,"dataClasses")
pc[, 4] fbatch fcond
"numeric" "factor" "factor"
$residuals
1 2 3 4 5 6
0.676033505 -0.658514298 1.179868113 -1.348393011 1.084563521 0.300738531
7 8 9 10 11 12
0.668547557 0.216140642 0.393492853 -0.356310152 -0.890955549 0.326366538
13 14 15 16 17 18
-0.290742637 -0.461343788 -0.006339403 0.283584088 -0.074497013 -0.438834197
19 20 21 22 23 24
0.599458914 -1.202864213 -0.886205122 0.295894184 1.169700492 -0.738251555
25 26 27 28 29 30
-1.377811845 -0.366983495 -1.283439404 -1.675269985 2.420075700 0.628267220
31 32 33 34 35 36
1.891149748 -0.475023583 0.369056676 -0.247296906 1.210210293 -1.406922987
37 38 39 40 41 42
-0.065842208 -1.123081231 2.060155170 -0.398381163 2.242488550 -0.758852498
43 44 45 46 47 48
-2.196476291 0.582209698 -0.753442289 0.756160747 0.493200050 -0.051397329
49 50 51 52 53 54
-0.559375155 -0.096658933 0.633778589 -3.347550286 -0.255192299 -0.700765984
55 56 57 58 59 60
1.821463075 -1.513095237 1.783774212 -0.491581306 1.305559403 1.105753283
$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.23141955 0.2981283 -0.7762415 0.4408727
fbatch2 0.39745613 0.3651311 1.0885300 0.2810238
fbatch3 -0.04281864 0.3651311 -0.1172692 0.9070663
fcond1 0.22641411 0.2981283 0.7594520 0.4507674
$aliased
(Intercept) fbatch2 fbatch3 fcond1
FALSE FALSE FALSE FALSE
$sigma
[1] 1.154646
$df
[1] 4 56 4
$r.squared
[1] 0.04019473
$adj.r.squared
[1] -0.01122341
$fstatistic
value numdf dendf
0.7817227 3.0000000 56.0000000
$cov.unscaled
(Intercept) fbatch2 fbatch3 fcond1
(Intercept) 0.06666667 -5.000000e-02 -5.000000e-02 -3.333333e-02
fbatch2 -0.05000000 1.000000e-01 5.000000e-02 -1.839961e-17
fbatch3 -0.05000000 5.000000e-02 1.000000e-01 -2.340556e-18
fcond1 -0.03333333 -1.839961e-17 -2.340556e-18 6.666667e-02
$call
lm(formula = pc[, 5] ~ fbatch + fcond)
$terms
pc[, 5] ~ fbatch + fcond
attr(,"variables")
list(pc[, 5], fbatch, fcond)
attr(,"factors")
fbatch fcond
pc[, 5] 0 0
fbatch 1 0
fcond 0 1
attr(,"term.labels")
[1] "fbatch" "fcond"
attr(,"order")
[1] 1 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
<environment: 0xc9f6db0>
attr(,"predvars")
list(pc[, 5], fbatch, fcond)
attr(,"dataClasses")
pc[, 5] fbatch fcond
"numeric" "factor" "factor"
$residuals
1 2 3 4 5 6
0.014654976 0.401223602 -0.404768253 1.091163931 0.215576187 1.069462223
7 8 9 10 11 12
-0.524442392 -0.457715317 0.316172519 0.028050858 -0.131363704 0.729068532
13 14 15 16 17 18
0.876444362 -0.773886975 -0.141427915 -1.611025195 -0.494940481 -0.006850571
19 20 21 22 23 24
0.020746241 -0.216142628 0.139564997 0.481066220 -0.903036108 1.743453156
25 26 27 28 29 30
-1.770321060 0.574808747 -0.320004549 0.836753682 0.052290436 -1.241243657
31 32 33 34 35 36
0.938143151 1.201496731 -0.412531447 -1.129584621 1.016750635 -1.367896424
37 38 39 40 41 42
0.109952917 1.422038943 -0.467118016 -0.904583734 -0.683746034 -1.687276819
43 44 45 46 47 48
1.032950098 -0.217697901 2.087959173 0.531984465 0.566096582 0.662533269
49 50 51 52 53 54
-1.324637126 -2.310875905 -2.626112274 -0.866543417 1.569150540 0.141658302
55 56 57 58 59 60
2.130727900 0.495851644 0.997323696 1.350007810 -1.051296342 -0.798057659
$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.1116920 0.2764076 -0.4040842 0.68768991
fbatch2 -0.2357319 0.3385288 -0.6963422 0.48909486
fbatch3 -0.1890961 0.3385288 -0.5585818 0.57867393
fcond1 0.5066025 0.2764076 1.8328095 0.07214897
$aliased
(Intercept) fbatch2 fbatch3 fcond1
FALSE FALSE FALSE FALSE
$sigma
[1] 1.070522
$df
[1] 4 56 4
$r.squared
[1] 0.0651571
$adj.r.squared
[1] 0.01507623
$fstatistic
value numdf dendf
1.301038 3.000000 56.000000
$cov.unscaled
(Intercept) fbatch2 fbatch3 fcond1
(Intercept) 0.06666667 -5.000000e-02 -5.000000e-02 -3.333333e-02
fbatch2 -0.05000000 1.000000e-01 5.000000e-02 -1.839961e-17
fbatch3 -0.05000000 5.000000e-02 1.000000e-01 -2.340556e-18
fcond1 -0.03333333 -1.839961e-17 -2.340556e-18 6.666667e-02
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.