stan.models: stan.models

Description Usage Format Examples

Description

data.frame containing the structure of the github repository https://github.com/stan-dev/example-models that contains examples to run STAN models in R from the book by Gelman and Hill 'Data Analysis Using Regression Analysis and Multilevel/Hierarchical Models'.

Usage

1

Format

An object of class "data.frame"

Examples

1
2

Example output

Warning message:
In data(stan.models) : data set 'stan.models' not found
    chapter                                                       r.files
1         3                                            3.1_OnePredictor.R
2         3                                            3.1_OnePredictor.R
3         3                                      3.2_MultiplePredictors.R
4         3                                            3.3_Interactions.R
5         3                                           3.4_StatInference.R
6         3                                           3.5_GraphDisplays.R
7         3                                           3.5_GraphDisplays.R
8         3                                           3.5_GraphDisplays.R
9         3                                             3.6_Diagnostics.R
10        4                                   4.1_LinearTransformations.R
11        4                                 4.2_Centering&Standardizing.R
12        4                                 4.2_Centering&Standardizing.R
13        4                                 4.2_Centering&Standardizing.R
14        4                                 4.2_Centering&Standardizing.R
15        4                                      4.4_LogTransformations.R
16        4                                      4.4_LogTransformations.R
17        4                                      4.4_LogTransformations.R
18        4                                      4.4_LogTransformations.R
19        4                                    4.5_OtherTransformations.R
20        4                           4.6_RegressionModelsForPrediction.R
21        4                           4.6_RegressionModelsForPrediction.R
22        4                           4.6_RegressionModelsForPrediction.R
23        4                           4.6_RegressionModelsForPrediction.R
24        4                           4.6_RegressionModelsForPrediction.R
25        4                           4.6_RegressionModelsForPrediction.R
26        5                      5.1_LogisticRegressionWithOnePredictor.R
27        5                      5.2_InterpretingLogisticRegressionCoef.R
28        5                     5.4_LogisticRegressionWellsinBangladesh.R
29        5                     5.4_LogisticRegressionWellsinBangladesh.R
30        5                     5.4_LogisticRegressionWellsinBangladesh.R
31        5                      5.5_LogisticRegressionWithInteractions.R
32        5                      5.5_LogisticRegressionWithInteractions.R
33        5                      5.5_LogisticRegressionWithInteractions.R
34        5                      5.5_LogisticRegressionWithInteractions.R
35        5                      5.5_LogisticRegressionWithInteractions.R
36        5                             5.6_EvaluatingCheckingComparing.R
37        5                             5.6_EvaluatingCheckingComparing.R
38        5                            5.7_AveragePredictiveComparisons.R
39        5                            5.7_AveragePredictiveComparisons.R
40        5                            5.8_IdentifiabilityAndSeparation.R
41        6                                        6.4_ProbitRegression.R
42        6                                          6.7_MoreComplexGLM.R
43        6                                          6.7_MoreComplexGLM.R
44        6                                6.8_ConstructiveChoiceModels.R
45        7                       7.3_SimulationForNonLinearPredictions.R
46        7                              7.4_PredictiveSimulationForGLM.R
47        7                              7.4_PredictiveSimulationForGLM.R
48        7                              7.4_PredictiveSimulationForGLM.R
49        8             8.2_FakeDataSimulationToUnderstandResidualPlots.R
50        8                            8.3_SimulatingFromTheFittedModel.R
51        8                            8.3_SimulatingFromTheFittedModel.R
52        8                            8.3_SimulatingFromTheFittedModel.R
53        8        8.4_PredictiveSimulationToCheckFitOfTimeSeriesModels.R
54        9                                   9.3_RandomizedExperiments.R
55        9                                   9.3_RandomizedExperiments.R
56        9              9.4_TreatmentInteractionsAndPoststratification.R
57        9              9.4_TreatmentInteractionsAndPoststratification.R
58        9              9.4_TreatmentInteractionsAndPoststratification.R
59        9              9.4_TreatmentInteractionsAndPoststratification.R
60        9                                    9.5_ObservationalStudies.R
61       10             10.4_LackOfOverlapWhenTreat.AssignmentIsUnknown.R
62       10             10.4_LackOfOverlapWhenTreat.AssignmentIsUnknown.R
63       10             10.4_LackOfOverlapWhenTreat.AssignmentIsUnknown.R
64       10             10.4_LackOfOverlapWhenTreat.AssignmentIsUnknown.R
65       10                                   10.5_CasualEffectsUsingIV.R
66       10                                   10.5_CasualEffectsUsingIV.R
67       10                               10.6_IVinaRegressionFramework.R
68       10                               10.6_IVinaRegressionFramework.R
69       12                         12.2_PartialPoolingWithNoPredictors.R
70       12                           12.3_PartialPoolingWithPredictors.R
71       12                           12.3_PartialPoolingWithPredictors.R
72       12                                          12.4_FittingMLMinR.R
73       12                                          12.4_FittingMLMinR.R
74       12                                             12.8_Prediction.R
75       13                               13.1_VaryingIntercepts&Slopes.R
76       13                               13.1_VaryingIntercepts&Slopes.R
77       13                               13.1_VaryingIntercepts&Slopes.R
78       13                               13.1_VaryingIntercepts&Slopes.R
79       13      13.4_UnderstandingCorrelationsBetweenIntercepts&Slopes.R
80       13      13.4_UnderstandingCorrelationsBetweenIntercepts&Slopes.R
81       13                                       13.5_Non-NestedModels.R
82       13                                       13.5_Non-NestedModels.R
83       14                   14.1_State-LevelOpinionsFromNationalPolls.R
84       14                   14.1_State-LevelOpinionsFromNationalPolls.R
85       19 19.4_RedundantParameters&IntentionallyNonidentifiableModels.R
86       19 19.4_RedundantParameters&IntentionallyNonidentifiableModels.R
87       19 19.4_RedundantParameters&IntentionallyNonidentifiableModels.R
88       19 19.4_RedundantParameters&IntentionallyNonidentifiableModels.R
89       19                                     19.5_ParameterExpansion.R
90       19                                     19.5_ParameterExpansion.R
91       20     20.5_MultilevelPowerCalculationUsingFake-DataSimulation.R
92       20     20.5_MultilevelPowerCalculationUsingFake-DataSimulation.R
93       21                  21.6_SummarizingtheAmmountofPartialPooling.R
94       21                  21.6_SummarizingtheAmmountofPartialPooling.R
95       21            21.7_AddingAPredictorCanIncreaseResidualVariance.R
96       21            21.7_AddingAPredictorCanIncreaseResidualVariance.R
97       21            21.7_AddingAPredictorCanIncreaseResidualVariance.R
98       22                                      22.4_DoingANOVUsingMLM.R
99       23                      23.1_MultilevelAspectsofDataCollection.R
100      23                      23.1_MultilevelAspectsofDataCollection.R
101      23                      23.1_MultilevelAspectsofDataCollection.R
102      23                      23.1_MultilevelAspectsofDataCollection.R
103      23                      23.1_MultilevelAspectsofDataCollection.R
104      24                           24.2_BehavioralLearningExperiment.R
105      25                       25.4_RadomImputationofaSingleVariable.R
106      25                       25.4_RadomImputationofaSingleVariable.R
107      25                       25.4_RadomImputationofaSingleVariable.R
108      25                       25.4_RadomImputationofaSingleVariable.R
109      25                    25.5_ImputationofSeveralMissingVariables.R
                           stan.files                  stan.obj.output
1                 kidscore_momhs.stan                   kidscore_momhs
2                 kidscore_momiq.stan                   kidscore_momiq
3              kidiq_multi_preds.stan                kidiq_multi_preds
4              kidiq_interaction.stan                kidiq_interaction
5              kidiq_multi_preds.stan                kidiq_multi_preds
6                 kidscore_momiq.stan                        stanfit.2
7              kidiq_multi_preds.stan                        stanfit.3
8              kidiq_interaction.stan                        stanfit.4
9                 kidscore_momiq.stan                kidscore_momiq.sf
10                   earn_height.stan                      earn_height
11             kidiq_interaction.stan                kidiq_interaction
12           kidiq_interaction_c.stan              kidiq_interaction_c
13          kidiq_interaction_c2.stan             kidiq_interaction_c2
14           kidiq_interaction_z.stan              kidiq_interaction_z
15                logearn_height.stan                logearn_height.sf
16              log10earn_height.stan              log10earn_height.sf
17           logearn_height_male.stan           logearn_height_male.sf
18             logearn_logheight.stan             logearn_logheight.sf
19              kidscore_momwork.stan              kidscore_momwork.sf
20                      mesquite.stan                      mesquite.sf
21                  mesquite_log.stan                  mesquite_log.sf
22               mesquite_volume.stan               mesquite_volume.sf
23                  mesquite_vas.stan                  mesquite_vas.sf
24                   mesquite_va.stan                   mesquite_va.sf
25                 mesquite_vash.stan                 mesquite_vash.sf
26                     nes_logit.stan                     nes_logit.sf
27                     nes_logit.stan                               sf
28                    wells_dist.stan                    wells_dist.sf
29                 wells_dist100.stan                 wells_dist100.sf
30                 wells_d100ars.stan                 wells_d100ars.sf
31             wells_interaction.stan             wells_interaction.sf
32           wells_interaction_c.stan           wells_interaction_c.sf
33                  wells_daae_c.stan                  wells_daae_c.sf
34                   wells_dae_c.stan                   wells_dae_c.sf
35             wells_dae_inter_c.stan             wells_dae_inter_c.sf
36               wells_predicted.stan               wells_predicted.sf
37           wells_predicted_log.stan           wells_predicted_log.sf
38                     wells_dae.stan                     wells_dae.sf
39               wells_dae_inter.stan               wells_dae_inter.sf
40                    separation.stan                    separation.sf
41                  wells_probit.stan                 wells_probit.sf1
42                     earnings1.stan                    earnings1.sf1
43                     earnings2.stan                    earnings2.sf1
44                   wells_logit.stan                  wells_logit.sf1
45                      congress.stan                     congress.sf1
46                         wells.stan                        wells.sf1
47                     earnings1.stan                    earnings1.sf1
48                     earnings2.stan                    earnings2.sf1
49                        grades.stan                       grades.sf1
50                    lightspeed.stan                   lightspeed.sf1
51                       roaches.stan                      roaches.sf1
52        roaches_overdispersion.stan       roaches_overdispersion.sf1
53                  unemployment.stan                 unemployment.sf1
54                   electric_tr.stan                             sf.1
55                electric_trpre.stan                             sf.2
56                   electric_tr.stan                   electric_tr.sf
57                electric_trpre.stan                electric_trpre.sf
58                electric_inter.stan                electric_inter.sf
59                electric_inter.stan                               sf
60                 electric_supp.stan                               sf
61                 ideo_two_pred.stan                ideo_two_pred.sf1
62                 ideo_two_pred.stan                ideo_two_pred.sf2
63             ideo_interactions.stan            ideo_interactions.sf1
64                  ideo_reparam.stan                 ideo_reparam.sf1
65             sesame_one_pred_a.stan            sesame_one_pred_a.sf1
66             sesame_one_pred_a.stan            sesame_one_pred_b.sf1
67             sesame_one_pred_a.stan           sesame_one_pred_2a.sf1
68             sesame_one_pred_a.stan           sesame_one_pred_2b.sf1
69               radon_intercept.stan              radon_intercept.sf1
70           radon_complete_pool.stan          radon_complete_pool.sf1
71                 radon_no_pool.stan                radon_no_pool.sf1
72               radon_intercept.stan              radon_intercept.sf1
73                 radon_no_pool.stan                radon_no_pool.sf1
74                   radon_group.stan                 #radon_group.sf1
75                 radon_vary_si.stan                radon_vary_si.sf1
76                           y_x.stan                radon_no_pool.sf1
77                           y_x.stan          radon_complete_pool.sf1
78              radon_inter_vary.stan             radon_inter_vary.sf1
79              earnings_vary_si.stan             earnings_vary_si.sf1
80              earnings_vary_si.stan             earnings_vary_si.sf2
81                        pilots.stan                       pilots.sf1
82         earnings_latin_square.stan        earnings_latin_square.sf1
83                    election88.stan                   election88.sf1
84               election88_full.stan              election88_full.sf1
85                         radon.stan                        radon.sf1
86               radon_redundant.stan              radon_redundant.sf1
87                        pilots.stan                       pilots.sf1
88                    election88.stan                   election88.sf1
89              pilots_expansion.stan             pilots_expansion.sf1
90          election88_expansion.stan         election88_expansion.sf1
91                           hiv.stan                          hiv.sf1
92                     hiv_inter.stan                          hiv.sf2
93        radon_vary_intercept_a.stan       radon_vary_intercept_a.sf1
94        radon_vary_intercept_b.stan       radon_vary_intercept_b.sf1
95  radon_vary_intercept_nofloor.stan radon_vary_intercept_nofloor.sf1
96    radon_vary_intercept_floor.stan   radon_vary_intercept_floor.sf1
97   radon_vary_intercept_floor2.stan  radon_vary_intercept_floor2.sf1
98            anova_radon_nopred.stan           anova_radon_nopred.sf1
99                   electric_1a.stan                  electric_1a.sf1
100                  electric_1b.stan                  electric_1b.sf1
101                  electric_1c.stan                  electric_1c.sf1
102            electric_one_pred.stan            electric_one_pred.sf1
103         electric_multi_preds.stan         electric_multi_preds.sf1
104                         dogs.stan                         dogs.sf1
105                     earnings.stan                     earnings.sf1
106                     earnings.stan                     earnings.sf2
107                 earnings_pt1.stan                 earnings_pt1.sf1
108                 earnings_pt2.stan                 earnings_pt2.sf1
109                    earnings2.stan                    earnings2.sf1
                                                        model.type
1                                                    One predictor
2                                                    One predictor
3                          Multiple predictors with no interaction
4                             Multiple predictors with interaction
5                          Multiple predictors with no interaction
6                                                    One predictor
7                          Multiple predictors with no interaction
8                             Multiple predictors with interaction
9                                                    One predictor
10                                   A simple regression, raw data
11                  Multiple predictors with interaction, raw data
12                                                       Centering
13            Centering based on an understandable reference point
14                                                   Standardizing
15                                             Log transformations
16                                             Log transformations
17                                             Log transformations
18                                             Log transformations
19                                              Discrete predictor
20                                           Models for prediction
21                                           Models for prediction
22                                           Models for prediction
23                                           Models for prediction
24                                           Models for prediction
25                                           Models for prediction
26                                                   One predictor
27                                                   One predictor
28                                                   One predictor
29                                                   One predictor
30                         Multiple predictors with no interaction
31                             Multiple predictors with interction
32                             Multiple predictors with interction
33                             Multiple predictors with interction
34                             Multiple predictors with interction
35                             Multiple predictors with interction
36                             Multiple predictors with interction
37                             Multiple predictors with interction
38                         Multiple predictors with no interaction
39                             Multiple predictors with interction
40                                                   One predictor
41                                                   One predictor
42                         Multiple predictors with no interaction
43                                             Log transformations
44                                                   One predictor
45                         Multiple predictors with no interaction
46                                                   One predictor
47                         Multiple predictors with no interaction
48                                             Log transformations
49                                                   One predictor
50                                                 Zero predictors
51                                Poisson regression with exposure
52                               Poisson overdispersion regression
53                                                   One predictor
54                                                   One predictor
55                         Multiple predictors without interaction
56                                                   One predictor
57                         Multiple predictors without interaction
58                            Multiple predictors with interaction
59                            Multiple predictors with interaction
60                         Multiple predictors without interaction
61                         Multiple predictors without interaction
62                         Multiple predictors without interaction
63                            Multiple predictors with interaction
64                         Multiple predictors without interaction
65                                                   One predictor
66                                                   One predictor
67                                                   One predictor
68                                                   One predictor
69                         Multilevel model with varying intercept
70                                                   One predictor
71                         Multilevel model with varying intercept
72                         Multilevel model with varying intercept
73                         Multilevel model with varying intercept
74                         Multilevel model with varying intercept
75               Multilevel model with varying slope and intercept
76                                                   One predictor
77                                                   One predictor
78               Multilevel model with varying slope and intercept
79               Multilevel model with varying slope and intercept
80               Multilevel model with varying slope and intercept
81            Multilevel model with several group level predictors
82            Multilevel model with several group level predictors
83                         Multilevel model with varying intercept
84            Multilevel model with several group level predictors
85                         Multilevel model with varying intercept
86                Multilevel model with redundant parameterization
87            Multilevel model with several group level predictors
88                         Multilevel model with varying intercept
89                       Multilevel model with parameter expansion
90                       Multilevel model with parameter expansion
91               Multilevel model with varying intercept and slope
92    Multilevel model with group level predictors and interaction
93                         Multilevel model with varying intercept
94                         Multilevel model with varying intercept
95                         Multilevel model with varying intercept
96                         Multilevel model with varying intercept
97                         Multilevel model with varying intercept
98                         Multilevel model with varying intercept
99               Multilevel model with varying slope and intercept
100              Multilevel model with varying slope and intercept
101              Multilevel model with varying slope and intercept
102                                Linear model with one predictor
103  Linear model with multiple predictors and without interaction
104                                               Multilevel model
105                    Single level model with multiple predictors
106                    Single level model with multiple predictors
107                    Single level model with multiple predictors
108                    Single level model with multiple predictors
109                    Single level model with multiple predictors
                                                                  model.eq
1                                                   lm(kid_score ~ mom_hs)
2                                                   lm(kid_score ~ mom_iq)
3                                          lm(kid_score ~ mom_hs + mom_iq)
4                                  lm(kid_score ~ mom_hs + mom_iq + mom_hs
5                                          lm(kid_score ~ mom_hs + mom_iq)
6                                                   lm(kid_score ~ mom_iq)
7                                          lm(kid_score ~ mom_hs + mom_iq)
8                                  lm(kid_score ~ mom_hs + mom_iq + mom_hs
9                                                   lm(kid_score ~ mom_iq)
10                                                       lm(earn ~ height)
11                                 lm(kid_score ~ mom_hs + mom_iq + mom_hs
12                                      lm(kid_score ~ c_mom_hs + c_mom_iq
13                                    lm(kid_score ~ c2_mom_hs + c2_mom_iq
14                                      lm(kid_score ~ z_mom_hs + z_mom_iq
15                                                  lm(log(earn) ~ height)
16                                                lm(log10(earn) ~ height)
17                                           lm(log(earn) ~ height + male)
18                                      lm(log(earn) ~ log(height) + male)
19                                     lm(kid_score ~ as.factor(mom_work))
20                lm(weight ~ diam1 + diam2 + canopy_height + total_height
21                                lm(log(weight) ~ log(diam1) + log(diam2)
22                                    lm(log(weight) ~ log(canopy_volume))
23                  lm(log(weight) ~ log(canopy_volume) + log(canopy_area)
24                                     lm(log(weight) ~ log(canopy_volume)
25                  lm(log(weight) ~ log(canopy_volume) + log(canopy_area)
26                       glm(vote ~ income, family=binomial(link="logit"))
27                       glm(vote ~ income, family=binomial(link="logit"))
28                     glm(switched ~ dist, family=binomial(link="logit"))
29                 glm(switched ~ dist/100, family=binomial(link="logit"))
30       glm(switched ~ dist/100 + arsenic, family=binomial(link="logit"))
31                            glm(switched ~ dist/100 + arsenic + dist/100
32                                    glm(switched ~ c_dist100 + c_arsenic
33                        glm(switched ~ c_dist100 + c_arsenic + c_dist100
34                        glm(switched ~ c_dist100 + c_arsenic + c_dist100
35                          glm(switched ~ c_dist100 + c_arsenic + c_educ4
36                          glm(switched ~ c_dist100 + c_arsenic + c_educ4
37                      glm(switched ~ c_dist100 + c_log_arsenic + c_educ4
38                             glm(switched ~ dist/100 + arsenic + educ/4,
39                              glm(switched ~ dist/100 + arsenic + educ/4
40                               glm(y ~ x, family=binomial(link="logit"))
41                    glm(switc ~ dist100, family=binomial(link="probit"))
42            glm(earn_pos ~ height + male, family=binomial(link="logit"))
43                                       lm(log(earnings) ~ height + male)
44                     glm(switc ~ dist100, family=binomial(link="logit"))
45                                   lm(vote_88 ~ vote_86 + incumbency_88)
46                        glm(switc ~ dist, family=binomial(link="logit"))
47            glm(earn_pos ~ height + male, family=binomial(link="logit"))
48                                       lm(log(earnings) ~ height + male)
49                                                     lm(final ~ midterm)
50                                                               lm(y ~ 1)
51                   glm (y ~ roach1 + treatment + senior, family=poisson,
52                                    glm(y ~ roach1 + treatment + senior,
53                                                           lm(y ~ y_lag)
54                                               lm(post_test ~ treatment)
55                                    lm(post_test ~ treatment + pre_test)
56                                               lm(post_test ~ treatment)
57                                    lm(post_test ~ treatment + pre_test)
58                         lm(post_test ~ treatment + pre_test + treatment
59                         lm(post_test ~ treatment + pre_test + treatment
60                                         lm(post_test ~ supp + pre_test)
61                                                  lm(score1 ~ party + x)
62                                                  lm(score1 ~ party + x)
63                                           lm(score1 ~ party + x + party
64                                            lm(score1 ~ party + z1 + z2)
65                                                lm(watched ~ encouraged)
66                                                lm(watched ~ encouraged)
67                                                lm(watched ~ encouraged)
68                                                lm(watched ~ encouraged)
69                                              lmer(y ~ 1 + (1 | county))
70                                                               lm(y ~ x)
71                                              lmer(y ~ x + (1 | county))
72                                              lmer(y ~ 1 + (1 | county))
73                                              lmer(y ~ x + (1 | county))
74                                          lmer(y ~ x + u + (1 | county))
75                                          lmer(y ~ 1 + (1 + x | county))
76                                                               lm(y ~ x)
77                                                               lm(y ~ x)
78                                                          lmer(y ~ u + u
79                                lmer(log(earn) ~ 1 + (1 + height | eth))
80                                lmer(log(earn) ~ 1 + (1 + height | eth))
81                              lmer(y ~ 1 + (1 | group) + (1 | scenario))
82                              lmer(y ~ 1 + (1 + x | eth) + (1 + x | age)
83  glmer(y ~ black + female + (1 | state), family=binomial(link="logit"))
84      glmer(y ~ black + female + v_prev_full + (1 | age) + (1 | age_edu)
85                                              lmer(y ~ 1 + (1 | county))
86                                              lmer(y ~ 1 + (1 | county))
87                            lmer(y ~1 + (1 | treatment) + (1 | airport))
88                                       glmer(y ~ black + female + female
89                           lmer(y ~ 1 + (1 | treatment) + (1 | airport))
90                                       glmer(y ~ black + female + female
91                                       lmer(y ~ 1 + (1 + time | person))
92                                                           lmer(y ~ time
93                                              lmer(y ~ x + (1 | county))
94                                              lmer(y ~ x + (1 | county))
95                                              lmer(y ~ u + (1 | county))
96                                          lmer(y ~ u + x + (1 | county))
97                                 lmer(y ~ u + x + x_mean + (1 | county))
98                                              lmer(y ~ 1 + (1 | county))
99                          lmer(y ~ 1 + (1 | pair) + (treatment | grade))
100                            lmer(y ~ treatment + pre_test + (1 | pair))
101              lmer(y ~ 1 + (1 | pair) + (treatment + pre_test | grade))
102                                              lm(post_test ~ treatment)
103                                   lm(post_test ~ treatment + pre_test)
104            glmer(y ~ n_avoid + n_shock, family=binomial(link="logit"))
105         lm(earnings ~ male + over65 + white + immig + educ_r + workmos
106         lm(earnings ~ male + over65 + white + immig + educ_r + workmos
107        glm(earnings ~ male + over65 + white + immig + educ_r + any_ssi
108         lm(earnings ~ male + over65 + white + immig + educ_r + any_ssi
109        lm(earnings ~ interest + male + over65 + white + immig + educ_r
    reg.type
1         lm
2         lm
3         lm
4         lm
5         lm
6         lm
7         lm
8         lm
9         lm
10        lm
11        lm
12        lm
13        lm
14        lm
15        lm
16        lm
17        lm
18        lm
19        lm
20        lm
21        lm
22        lm
23        lm
24        lm
25        lm
26       glm
27       glm
28       glm
29       glm
30       glm
31       glm
32       glm
33       glm
34       glm
35       glm
36       glm
37       glm
38       glm
39       glm
40       glm
41       glm
42       glm
43        lm
44       glm
45        lm
46       glm
47       glm
48        lm
49        lm
50        lm
51       glm
52       glm
53        lm
54        lm
55        lm
56        lm
57        lm
58        lm
59        lm
60        lm
61        lm
62        lm
63        lm
64        lm
65        lm
66        lm
67        lm
68        lm
69      lmer
70        lm
71      lmer
72      lmer
73      lmer
74      lmer
75      lmer
76        lm
77        lm
78      lmer
79      lmer
80      lmer
81      lmer
82      lmer
83     glmer
84     glmer
85      lmer
86      lmer
87      lmer
88     glmer
89      lmer
90     glmer
91      lmer
92      lmer
93      lmer
94      lmer
95      lmer
96      lmer
97      lmer
98      lmer
99      lmer
100     lmer
101     lmer
102       lm
103       lm
104    glmer
105       lm
106       lm
107      glm
108       lm
109       lm

d3Tree documentation built on June 20, 2017, 9:15 a.m.