Collect the coefficients and some qualifying statistics of linear models and organize it in a table for comparison and reporting. The function supports linear and general linear models.

TMod(..., FUN = NULL, order = NA)

ModSummary(x, ...)

# S3 method for lm
ModSummary(x, conf.level = 0.95, ...)
# S3 method for glm
ModSummary(x, conf.level = 0.95, use.profile = TRUE, ...)

# S3 method for TMod
plot(x, terms = NULL, intercept = FALSE, ...)
# S3 method for TMod
print(x, digits = 3, na.form = "-", ...)

Arguments

x

a (general) linear model object.

...

a list of (general) linear models.

conf.level

the level for the confidence intervals.

FUN

function with arguments est, se, tval, pval, lci, uci to display the coefficients. The default function will display the coefficient and significance stars for the p-values.

order

row of the results table to be used as order for the models (as typically "AIC"). Can be any label in the first column of the results table. Default is NA for no special order.

terms

a vector with the terms of the model formula to be plotted. By default this will be all of them.

use.profile

logical. Defines if profile approach should be used, which normally is a good choice for small datasets. Calculating profile can however take ages for large datasets and not be necessary there. So we can fallback to normal confidence intervals.

intercept

logical, defining whether the intercept should be plotted (default is FALSE).

digits

integer, the desired (fixed) number of digits after the decimal point. Unlike formatC you will always get this number of digits even if the last digit is 0.

na.form

character, string specifying how NAs should be specially formatted. If set to NULL (default) no special action will be taken.

Details

In order to compare the coefficients of linear models, the user is left to his own devices. R offers no support in this respect. TMod() jumps into the breach and displays the coefficients of several models in tabular form. For this purpose, different quality indicators for the models are displayed, so that a comprehensive comparison of the models is possible. In particular, it is easy to see the effect that adding or omitting variables has on forecast quality.

A plot function for a TMod object will produce a dotchart with the coefficients and their confidence intervals.

Value

character table

Author

Andri Signorell <andri@signorell.net>

See also

Examples

r.full <- lm(Fertility ~ . , swiss)
r.nox <- lm(Fertility ~ . -Examination - Catholic, swiss)
r.grp <- lm(Fertility ~ . -Education - Catholic + CutQ(Catholic), swiss)
r.gam <- glm(Fertility ~ . , swiss, family=Gamma(link="identity"))
r.gama <- glm(Fertility ~ .- Agriculture , swiss, family=Gamma(link="identity"))
r.gaml <- glm(Fertility ~ . , swiss, family=Gamma(link="log"))

TMod(r.full, r.nox, r.grp, r.gam, r.gama, r.gaml)
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Waiting for profiling to be done...
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Waiting for profiling to be done...
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#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Waiting for profiling to be done...
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#>                coef   r.full        r.nox        r.grp        r.gam    
#> 1       (Intercept)   66.915 ***   51.101 ***   53.411 ***   63.709 ***
#> 2       Agriculture   -0.172 *     -0.026       -0.096       -0.175 *  
#> 3       Examination   -0.258        -           -0.872 ***   -0.129    
#> 4         Education   -0.871 ***   -0.857 ***    -           -0.944 ***
#> 5          Catholic    0.104 **     -            -            0.106 ** 
#> 6  Infant.Mortality    1.077 **     1.493 **     1.796 ***    1.174 ** 
#> 7  CutQ(Catholic)Q2    -            -           -0.035        -        
#> 8  CutQ(Catholic)Q3    -            -           -5.780        -        
#> 9  CutQ(Catholic)Q4    -            -            5.939        -        
#> 10              ---                                                    
#> 11        r.squared    0.707        0.566        0.611        -        
#> 12    adj.r.squared    0.671        0.536        0.552        -        
#> 13            sigma    7.165        8.511        8.359        -        
#> 14           logLik -156.036     -165.243     -162.699     -156.506    
#> 15          logLik0    -            -            -         -186.992    
#> 16               G2    -            -            -           60.971    
#> 17         deviance 2105.043     3114.635     2795.124        -        
#> 18              AIC  326.072      340.485      341.398      327.012    
#> 19              BIC  339.023      349.736      356.199      339.963    
#> 20            numdf    5            3            6            7        
#> 21            dendf   41           43           40            -        
#> 22                N   47           47           47           47        
#> 23           n vars    5            3            4            5        
#> 24           n coef    6            4            7            6        
#> 25                F   19.761       18.699       10.454        -        
#> 26                p    5.594e-10    0.000        0.000        -        
#> 27              MAE    5.321        6.826        6.079        5.330    
#> 28             MAPE    0.079        0.098        0.095        0.078    
#> 29              MSE   44.788       66.269       59.471       45.342    
#> 30             RMSE    6.692        8.141        7.712        6.734    
#> 31         McFadden    -            -            -            0.163    
#> 32      McFaddenAdj    -            -            -            0.131    
#> 33       Nagelkerke    -            -            -            0.727    
#> 34         CoxSnell    -            -            -            0.727    
#>      r.gama       r.gaml    
#> 1    48.790 ***    4.184 ***
#> 2     -           -0.002 *  
#> 3     0.050       -0.003    
#> 4    -0.808 ***   -0.015 ***
#> 5     0.089 *      0.001 *  
#> 6     1.290 **     0.017 ** 
#> 7     -            -        
#> 8     -            -        
#> 9     -            -        
#> 10                          
#> 11    -            -        
#> 12    -            -        
#> 13    -            -        
#> 14 -159.674     -157.224    
#> 15 -186.992     -186.992    
#> 16   54.636       59.534    
#> 17    -            -        
#> 18  331.347      328.449    
#> 19  342.448      341.400    
#> 20    6            7        
#> 21    -            -        
#> 22   47           47        
#> 23    4            5        
#> 24    5            6        
#> 25    -            -        
#> 26    -            -        
#> 27    5.869        5.458    
#> 28    0.086        0.080    
#> 29   52.015       47.361    
#> 30    7.212        6.882    
#> 31    0.146        0.159    
#> 32    0.119        0.127    
#> 33    0.688        0.718    
#> 34    0.687        0.718    

# display confidence intervals
TMod(r.full, r.nox, r.gam, FUN = function(est, se, tval, pval, lci, uci){
  gettextf("%s [%s, %s]",
           Format(est, fmt=Fmt("num")),
           Format(lci, digits=3),
           Format(uci, digits=2)
           )
})
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Waiting for profiling to be done...
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#>                coef               r.full                    r.nox    
#> 1       (Intercept)   66.915 [45.294, 88.54]   51.101 [28.928, 73.27]
#> 2       Agriculture   -0.172 [-0.314, -0.03]   -0.026 [-0.173, 0.12] 
#> 3       Examination   -0.258 [-0.771, 0.25]     -                    
#> 4         Education   -0.871 [-1.241, -0.50]   -0.857 [-1.205, -0.51]
#> 5          Catholic    0.104 [0.033, 0.18]      -                    
#> 6  Infant.Mortality    1.077 [0.306, 1.85]      1.493 [0.608, 2.38]  
#> 7               ---                                                  
#> 8         r.squared    0.707                    0.566                
#> 9     adj.r.squared    0.671                    0.536                
#> 10            sigma    7.165                    8.511                
#> 11           logLik -156.036                 -165.243                
#> 12          logLik0    -                        -                    
#> 13               G2    -                        -                    
#> 14         deviance 2105.043                 3114.635                
#> 15              AIC  326.072                  340.485                
#> 16              BIC  339.023                  349.736                
#> 17            numdf    5                        3                    
#> 18            dendf   41                       43                    
#> 19                N   47                       47                    
#> 20           n vars    5                        3                    
#> 21           n coef    6                        4                    
#> 22                F   19.761                   18.699                
#> 23                p    5.594e-10                0.000                
#> 24              MAE    5.321                    6.826                
#> 25             MAPE    0.079                    0.098                
#> 26              MSE   44.788                   66.269                
#> 27             RMSE    6.692                    8.141                
#> 28         McFadden    -                        -                    
#> 29      McFaddenAdj    -                        -                    
#> 30       Nagelkerke    -                        -                    
#> 31         CoxSnell    -                        -                    
#>                   r.gam    
#> 1    63.709 [44.294, 83.44]
#> 2    -0.175 [-0.318, -0.04]
#> 3    -0.129 [-0.626, 0.36] 
#> 4    -0.944 [-1.252, -0.63]
#> 5     0.106 [0.035, 0.18]  
#> 6     1.174 [0.479, 1.84]  
#> 7                          
#> 8     -                    
#> 9     -                    
#> 10    -                    
#> 11 -156.506                
#> 12 -186.992                
#> 13   60.971                
#> 14    -                    
#> 15  327.012                
#> 16  339.963                
#> 17    7                    
#> 18    -                    
#> 19   47                    
#> 20    5                    
#> 21    6                    
#> 22    -                    
#> 23    -                    
#> 24    5.330                
#> 25    0.078                
#> 26   45.342                
#> 27    6.734                
#> 28    0.163                
#> 29    0.131                
#> 30    0.727                
#> 31    0.727                


# cbind interface is not supported!!
# d.titanic <- reshape(as.data.frame(Titanic),
#                       idvar = c("Class","Sex","Age"),
#                       timevar="Survived",
#                       direction = "wide")
#
# r.glm0 <- glm(cbind(Freq.Yes, Freq.No) ~ 1, data=d.titanic, family="binomial")
# r.glm1 <- glm(cbind(Freq.Yes, Freq.No) ~ Class, data=d.titanic, family="binomial")
# r.glm2 <- glm(cbind(Freq.Yes, Freq.No) ~ ., data=d.titanic, family="binomial")

d.titanic <- Untable(Titanic)

r.glm0 <- glm(Survived ~ 1, data=d.titanic, family="binomial")
r.glm1 <- glm(Survived ~ Class, data=d.titanic, family="binomial")
r.glm2 <- glm(Survived ~ ., data=d.titanic, family="binomial")

TMod(r.glm0, r.glm1, r.glm2)
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Waiting for profiling to be done...
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Waiting for profiling to be done...
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#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Waiting for profiling to be done...
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
#>             coef    r.glm0        r.glm1        r.glm2    
#> 1    (Intercept)    -0.740 ***     0.509 ***     0.685 *  
#> 2       Class2nd     -            -0.856 ***    -1.018 ***
#> 3       Class3rd     -            -1.596 ***    -1.778 ***
#> 4      ClassCrew     -            -1.664 ***    -0.858 ***
#> 5      SexFemale     -             -             2.420 ***
#> 6       AgeAdult     -             -            -1.062 ***
#> 7            ---                                          
#> 8         logLik -1384.728     -1294.278     -1105.031    
#> 9        logLik0 -1384.728     -1384.728     -1384.728    
#> 10            G2    -0.000       180.901       559.396    
#> 11           AIC  2771.457      2596.555      2222.061    
#> 12           BIC  2777.153      2619.342      2256.241    
#> 13         numdf     1             4             6        
#> 14             N  2201          2201          2201        
#> 15        n vars     0             1             3        
#> 16      McFadden     0.000         0.065         0.202    
#> 17   McFaddenAdj    -0.001         0.062         0.198    
#> 18    Nagelkerke     0.000         0.110         0.314    
#> 19      CoxSnell     0.000         0.079         0.224    
#> 20 Kendall Tau-a     0.000         0.124         0.227    
#> 21  Somers Delta     0.000         0.283         0.519    
#> 22         Gamma     -             0.386         0.623    
#> 23         Brier     0.219         0.200         0.162    
#> 24             C     0.500         0.642         0.760    

# plot OddsRatios
d.pima <- MASS::Pima.tr2

r.a <- glm(type ~ npreg + bp + skin + bmi + ped + age, data=d.pima, family=binomial)
r.b <- glm(type ~ npreg + glu + bp + skin, data=d.pima, family=binomial)
r.c <- glm(type ~ npreg + age, data=d.pima, family=binomial)

or.a <- OddsRatio(r.a)
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.
or.b <- OddsRatio(r.b)
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#> Warning: This function will be moved to the package ModTools. Please update.
or.c <- OddsRatio(r.c)
#> Warning: This function will be moved to the package ModTools. Please update.
#> Warning: This function will be moved to the package ModTools. Please update.


# create the model table
tm <- TMod(m_A=or.a, m_B=or.b, m_C=or.c)
#> Warning: This function will be moved to the package ModTools. Please update.
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# .. and plotit
plot(tm, main="ORs for Models A, B, C", intercept=FALSE,
     pch=15, col=c(DescTools::hred, DescTools::hblue, DescTools::horange), 
     panel.first=abline(v=1, col="grey30"))