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Last data update: 2014.03.03

R: Fitting Common Models via 'lm'

adjust_lmList.formula

R Documentation

Fitting Common Models via `lm`

Description

Separate linear models are fit via lm similar to lmList, however, adjust_lmList can handle models where a factor takes only one level within a group. In this case, the formula is updated eliminating the offending factors from the formula for that group as the effect is absorbed into the intercept.

Usage

## S3 method for class 'formula'
adjust_lmList(object, data, pool)

Arguments

`object`	a linear formula such as that used by `lmList`, e.g. `y ~ x1 + ... + xn \| g`, where `g` is a grouping factor.
`data`	a data frame containing the variables in the model.
`pool`	a logical value that indicates whether the pooled standard deviation/error should be used.

References

Douglas Bates, Martin Maechler and Ben Bolker (2012). lme4: Linear mixed-effects models using S4 classes. R package version 0.999999-0.

Examples

data(Exam, package = 'mlmRev')
sepLM <- adjust_lmList(normexam ~ standLRT + sex + schgend | school, data = Exam)
confint(sepLM)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(HLMdiag)

Attaching package: 'HLMdiag'

The following object is masked from 'package:stats':

    covratio

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/HLMdiag/adjust_lmList.formula.Rd_%03d_medium.png", width=480, height=480)
> ### Name: adjust_lmList.formula
> ### Title: Fitting Common Models via 'lm'
> ### Aliases: adjust_lmList adjust_lmList,formula,data.frame-method
> ###   adjust_lmList.formula
> ### Keywords: models regression
> 
> ### ** Examples
> 
> data(Exam, package = 'mlmRev')
> sepLM <- adjust_lmList(normexam ~ standLRT + sex + schgend | school, data = Exam)
Warning message:
In lme4::lmList(formula = object, data = data) :
  Fitting failed for 65 group(s), probably because a factor only had one level
> confint(sepLM)
, , 1

                 2.5 %       97.5 %
(Intercept)  0.3263569  0.880487552
standLRT     0.5428713  0.866088363
sexM        -0.7062104 -0.005229246

, , 2

                2.5 %    97.5 %
(Intercept) 0.2741168 0.6904430
standLRT    0.5856914 0.9368854
sexM               NA        NA

, , 3

                 2.5 %    97.5 %
(Intercept)  0.1808845 0.8652867
standLRT     0.3506674 0.8180285
sexM        -0.3548285 0.4692764

, , 4

                  2.5 %      97.5 %
(Intercept) -0.01708563  0.48795787
standLRT     0.57293686  0.90154411
sexM        -0.73604554 -0.06961313

, , 5

                 2.5 %    97.5 %
(Intercept) -0.1595617 0.5173484
standLRT     0.3196197 1.0194057
sexM        -0.3122614 0.6787381

, , 6

                2.5 %    97.5 %
(Intercept) 0.3994135 0.8070153
standLRT    0.3429282 0.7277607
sexM               NA        NA

, , 7

                 2.5 %    97.5 %
(Intercept) 0.24328532 0.5537685
standLRT    0.06437063 0.4201863
sexM                NA        NA

, , 8

                 2.5 %    97.5 %
(Intercept) -0.1694081 0.1190189
standLRT     0.4359288 0.6988817
sexM                NA        NA

, , 9

                 2.5 %    97.5 %
(Intercept) -0.5163689 0.3113809
standLRT     0.1773889 0.6149736
sexM        -0.7367574 0.2919920

, , 10

                  2.5 %     97.5 %
(Intercept) -0.45804811 0.21709881
standLRT     0.02129566 0.57311913
sexM        -0.75500829 0.09317282

, , 11

                 2.5 %    97.5 %
(Intercept) 0.04520193 0.4867243
standLRT    0.26858390 0.6486871
sexM                NA        NA

, , 12

                 2.5 %     97.5 %
(Intercept) -0.1851760 0.41786999
standLRT     0.1568075 0.68324550
sexM        -0.8170397 0.06032129

, , 13

                 2.5 %    97.5 %
(Intercept) -0.3121936 0.1602812
standLRT     0.4231835 0.7842949
sexM        -0.5761591 0.1841319

, , 14

                 2.5 %      97.5 %
(Intercept) -0.2340343 0.063454982
standLRT     0.4823489 0.710977683
sexM        -0.4104064 0.006161141

, , 15

                 2.5 %     97.5 %
(Intercept) -0.3897919 0.05931406
standLRT     0.5468211 0.92725157
sexM        -0.4497958 0.16101075

, , 16

                 2.5 %     97.5 %
(Intercept) -0.5521980 -0.2190879
standLRT     0.2195726  0.5943072
sexM                NA         NA

, , 17

                 2.5 %       97.5 %
(Intercept) -0.2983521 0.0005841605
standLRT     0.3663959 0.6146511204
sexM        -0.4595705 0.1462777495

, , 18

                 2.5 %     97.5 %
(Intercept) -0.1933661 0.07868622
standLRT     0.1547744 0.56399159
sexM                NA         NA

, , 19

                 2.5 %     97.5 %
(Intercept) -0.1988869 0.51911911
standLRT     0.4110062 1.03191597
sexM        -0.7989017 0.02781329

, , 20

                  2.5 %    97.5 %
(Intercept) -0.06610851 0.6511977
standLRT     0.28592233 0.7516565
sexM        -0.50887093 0.4261859

, , 21

                 2.5 %    97.5 %
(Intercept) 0.09411429 0.4433261
standLRT    0.36417729 0.7448105
sexM                NA        NA

, , 22

                 2.5 %     97.5 %
(Intercept) -0.6429741 -0.1931720
standLRT     0.3718559  0.6694182
sexM        -0.3994458  0.2207079

, , 23

                 2.5 %     97.5 %
(Intercept) -1.0589335 -0.3542877
standLRT     0.1232313  0.6513788
sexM        -0.3858722  0.7645369

, , 24

                  2.5 %    97.5 %
(Intercept) -0.08440336 0.4398668
standLRT     0.13979257 0.6554386
sexM                 NA        NA

, , 25

                 2.5 %      97.5 %
(Intercept) -0.4681044 -0.06747851
standLRT     0.3696859  0.69442914
sexM                NA          NA

, , 26

                 2.5 %    97.5 %
(Intercept) -0.2127768 0.3459270
standLRT     0.3539255 0.7146563
sexM        -0.5282161 0.1576498

, , 27

                 2.5 %    97.5 %
(Intercept) -0.2432297 0.3136069
standLRT     0.3332213 0.8125156
sexM                NA        NA

, , 28

                  2.5 %     97.5 %
(Intercept) -0.99160002 -0.4200939
standLRT     0.02992496  0.4868472
sexM        -0.54519752  0.2678522

, , 29

                 2.5 %    97.5 %
(Intercept) 0.02893775 0.3799085
standLRT    0.22122253 0.5798091
sexM                NA        NA

, , 30

                 2.5 %    97.5 %
(Intercept) -0.1119115 0.3496121
standLRT     0.6086169 1.0031872
sexM                NA        NA

, , 31

                  2.5 %    97.5 %
(Intercept) -0.29519837 0.2167474
standLRT     0.09812043 0.7064471
sexM                 NA        NA

, , 32

                 2.5 %    97.5 %
(Intercept) -0.2725009 0.4884809
standLRT     0.4469030 0.8652109
sexM        -0.5656019 0.4015437

, , 33

                 2.5 %    97.5 %
(Intercept) -0.1308773 0.3760244
standLRT     0.3136608 0.7161246
sexM        -0.4852955 0.1893604

, , 34

                 2.5 %    97.5 %
(Intercept) -0.4280417 0.6917086
standLRT     0.5417207 0.9908155
sexM        -0.9782206 0.3229082

, , 35

                  2.5 %    97.5 %
(Intercept) -0.10733145 0.3707919
standLRT     0.08583033 0.7074766
sexM                 NA        NA

, , 36

                 2.5 %     97.5 %
(Intercept) -0.3814711 -0.0323657
standLRT     0.2899044  0.5867862
sexM                NA         NA

, , 37

                  2.5 %     97.5 %
(Intercept) -0.86303981 -0.1074051
standLRT    -0.04683207  0.5233799
sexM                 NA         NA

, , 38

                 2.5 %    97.5 %
(Intercept) -0.4117786 0.1964173
standLRT     0.4324098 0.8045009
sexM        -0.4869755 0.3172313

, , 39

                  2.5 %    97.5 %
(Intercept) -0.08580749 0.3408916
standLRT     0.26389329 0.6412903
sexM                 NA        NA

, , 40

                 2.5 %      97.5 %
(Intercept) -0.4229468 -0.07745003
standLRT     0.5610778  0.89149116
sexM                NA          NA

, , 41

                 2.5 %    97.5 %
(Intercept) 0.01591697 0.4090773
standLRT    0.28336164 0.6834597
sexM                NA        NA

, , 42

                  2.5 %    97.5 %
(Intercept) -0.07672777 0.5315250
standLRT     0.14768929 0.6177283
sexM        -0.64733724 0.1542706

, , 43

                 2.5 %     97.5 %
(Intercept) -0.3694495 0.06225094
standLRT     0.4825313 0.96690972
sexM        -2.2578769 0.68123642

, , 44

                 2.5 %      97.5 %
(Intercept) -0.6217776 -0.06703287
standLRT     0.1116875  0.62756630
sexM                NA          NA

, , 45

                 2.5 %    97.5 %
(Intercept) -0.3237111 0.1040984
standLRT     0.3568099 0.7762701
sexM        -0.7863768 0.5817425

, , 46

                 2.5 %     97.5 %
(Intercept) -0.7547097 -0.2589714
standLRT     0.2678466  0.6303908
sexM        -0.1240484  0.5266384

, , 47

                 2.5 %    97.5 %
(Intercept) -1.6414956 1.2884991
standLRT     0.4758159 0.8601886
sexM        -1.3279602 1.6270263

, , 48

                2.5 %   97.5 %
(Intercept) -13.63570  7.09154
standLRT    -31.80557 18.00264
sexM               NA       NA

, , 49

                  2.5 %    97.5 %
(Intercept) -0.08945059 0.1843917
standLRT     0.32895521 0.6401583
sexM                 NA        NA

, , 50

                 2.5 %      97.5 %
(Intercept) -0.5619947 -0.08856006
standLRT     0.5009351  0.84965420
sexM        -0.3444848  0.34067081

, , 51

                 2.5 %      97.5 %
(Intercept) -0.2170689  0.30425141
standLRT     0.1326133  0.48269456
sexM        -0.8343468 -0.05585432

, , 52

                2.5 %    97.5 %
(Intercept) 0.1982797 0.5777984
standLRT    0.5580361 0.9225023
sexM               NA        NA

, , 53

                2.5 %    97.5 %
(Intercept) 0.4057054 0.7817016
standLRT    0.8896918 1.2642644
sexM               NA        NA

, , 54

                2.5 %    97.5 %
(Intercept) -1.511635 0.3726510
standLRT    -0.884864 0.9272546
sexM        -1.190699 0.8842954

, , 55

                 2.5 %     97.5 %
(Intercept)  0.4582710 1.05665797
standLRT     0.4073517 0.81633769
sexM        -0.8087157 0.00864674

, , 56

                 2.5 %     97.5 %
(Intercept) -0.1066648 0.51413522
standLRT     0.5827576 1.12899891
sexM        -0.8709050 0.08854877

, , 57

                 2.5 %    97.5 %
(Intercept) -0.1432485 0.2243516
standLRT     0.4184475 0.8062908
sexM                NA        NA

, , 58

                  2.5 %    97.5 %
(Intercept) -0.03930461 0.4534591
standLRT     0.07650285 0.6350650
sexM                 NA        NA

, , 59

                 2.5 %     97.5 %
(Intercept) -1.0155664 -0.2701350
standLRT     0.1330872  0.5857961
sexM        -0.7713684  0.1124081

, , 60

                 2.5 %    97.5 %
(Intercept) 0.08844282 0.4154892
standLRT    0.45619221 0.8194257
sexM                NA        NA

, , 61

                 2.5 %    97.5 %
(Intercept) -0.3460901 0.2017394
standLRT     0.4529938 0.8327429
sexM        -0.3159877 0.4360368

, , 62

                 2.5 %     97.5 %
(Intercept) -0.1590656 0.39744840
standLRT     0.3210642 0.76124913
sexM        -0.6371948 0.06990985

, , 63

                  2.5 %    97.5 %
(Intercept)  0.38260418 1.1225002
standLRT    -0.05601729 0.6743487
sexM        -0.70073875 0.3999581

, , 64

                 2.5 %    97.5 %
(Intercept) -0.1709083 0.2458974
standLRT     0.5057029 0.9053449
sexM                NA        NA

, , 65

                 2.5 %       97.5 %
(Intercept) -0.3418580 -0.007942406
standLRT     0.4098036  0.727114837
sexM                NA           NA

attr(,"class")
[1] "adjust_lmList.confint"
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>

Fitting Common Models via lm