comparePred.RdPredicted values are obtained at the specified values of
primary for each object. If either object1 or
object2 have a grouping structure
(i.e. getGroups(object) is not NULL), predicted values
are obtained for each group. When both objects determine groups, the
group levels must be the same. If other covariates besides
primary are used in the prediction model, their group-wise averages
(numeric covariates) or most frequent values (categorical covariates)
are used to obtain the predicted values. The original observations are
also included in the returned object.
comparePred(object1, object2, primary, minimum, maximum,
length.out, level, ...)fitted model objects, from which predictions can
be extracted using the predict method.
an optional one-sided formula specifying the primary
covariate to be used to generate the augmented predictions. By
default, if a covariate can be extracted from the data used to generate
the objects (using getCovariate), it will be used as
primary.
an optional lower limit for the primary
covariate. Defaults to min(primary), after primary is
evaluated in the data used in fitting object1.
an optional upper limit for the primary
covariate. Defaults to max(primary), after primary is
evaluated in the data used in fitting object1.
an optional integer with the number of primary covariate values at which to evaluate the predictions. Defaults to 51.
an optional integer specifying the desired prediction level. Levels increase from outermost to innermost grouping, with level 0 representing the population (fixed effects) predictions. Only one level can be specified. Defaults to the innermost level.
some methods for the generic may require additional arguments.
a data frame with four columns representing, respectively, the values
of the primary covariate, the groups (if object does not have a
grouping structure, all elements will be 1), the predicted or
observed values, and the type of value in the third column: the
objects' names are used to classify the predicted values and
original is used for the observed values. The returned object
inherits from classes comparePred and augPred.
This function is generic; method functions can be written to handle
specific classes of objects. Classes which already have methods for
this function include: gls, lme, and lmList.
fm1 <- lme(distance ~ age * Sex, data = Orthodont, random = ~ age)
fm2 <- update(fm1, distance ~ age)
comparePred(fm1, fm2, length.out = 2)
#> age .groups distance .type
#> 1 8 M01 26.00000 original
#> 2 10 M01 25.00000 original
#> 3 12 M01 29.00000 original
#> 4 14 M01 31.00000 original
#> 5 8 M02 21.50000 original
#> 6 10 M02 22.50000 original
#> 7 12 M02 23.00000 original
#> 8 14 M02 26.50000 original
#> 9 8 M03 23.00000 original
#> 10 10 M03 22.50000 original
#> 11 12 M03 24.00000 original
#> 12 14 M03 27.50000 original
#> 13 8 M04 25.50000 original
#> 14 10 M04 27.50000 original
#> 15 12 M04 26.50000 original
#> 16 14 M04 27.00000 original
#> 17 8 M05 20.00000 original
#> 18 10 M05 23.50000 original
#> 19 12 M05 22.50000 original
#> 20 14 M05 26.00000 original
#> 21 8 M06 24.50000 original
#> 22 10 M06 25.50000 original
#> 23 12 M06 27.00000 original
#> 24 14 M06 28.50000 original
#> 25 8 M07 22.00000 original
#> 26 10 M07 22.00000 original
#> 27 12 M07 24.50000 original
#> 28 14 M07 26.50000 original
#> 29 8 M08 24.00000 original
#> 30 10 M08 21.50000 original
#> 31 12 M08 24.50000 original
#> 32 14 M08 25.50000 original
#> 33 8 M09 23.00000 original
#> 34 10 M09 20.50000 original
#> 35 12 M09 31.00000 original
#> 36 14 M09 26.00000 original
#> 37 8 M10 27.50000 original
#> 38 10 M10 28.00000 original
#> 39 12 M10 31.00000 original
#> 40 14 M10 31.50000 original
#> 41 8 M11 23.00000 original
#> 42 10 M11 23.00000 original
#> 43 12 M11 23.50000 original
#> 44 14 M11 25.00000 original
#> 45 8 M12 21.50000 original
#> 46 10 M12 23.50000 original
#> 47 12 M12 24.00000 original
#> 48 14 M12 28.00000 original
#> 49 8 M13 17.00000 original
#> 50 10 M13 24.50000 original
#> 51 12 M13 26.00000 original
#> 52 14 M13 29.50000 original
#> 53 8 M14 22.50000 original
#> 54 10 M14 25.50000 original
#> 55 12 M14 25.50000 original
#> 56 14 M14 26.00000 original
#> 57 8 M15 23.00000 original
#> 58 10 M15 24.50000 original
#> 59 12 M15 26.00000 original
#> 60 14 M15 30.00000 original
#> 61 8 M16 22.00000 original
#> 62 10 M16 21.50000 original
#> 63 12 M16 23.50000 original
#> 64 14 M16 25.00000 original
#> 65 8 F01 21.00000 original
#> 66 10 F01 20.00000 original
#> 67 12 F01 21.50000 original
#> 68 14 F01 23.00000 original
#> 69 8 F02 21.00000 original
#> 70 10 F02 21.50000 original
#> 71 12 F02 24.00000 original
#> 72 14 F02 25.50000 original
#> 73 8 F03 20.50000 original
#> 74 10 F03 24.00000 original
#> 75 12 F03 24.50000 original
#> 76 14 F03 26.00000 original
#> 77 8 F04 23.50000 original
#> 78 10 F04 24.50000 original
#> 79 12 F04 25.00000 original
#> 80 14 F04 26.50000 original
#> 81 8 F05 21.50000 original
#> 82 10 F05 23.00000 original
#> 83 12 F05 22.50000 original
#> 84 14 F05 23.50000 original
#> 85 8 F06 20.00000 original
#> 86 10 F06 21.00000 original
#> 87 12 F06 21.00000 original
#> 88 14 F06 22.50000 original
#> 89 8 F07 21.50000 original
#> 90 10 F07 22.50000 original
#> 91 12 F07 23.00000 original
#> 92 14 F07 25.00000 original
#> 93 8 F08 23.00000 original
#> 94 10 F08 23.00000 original
#> 95 12 F08 23.50000 original
#> 96 14 F08 24.00000 original
#> 97 8 F09 20.00000 original
#> 98 10 F09 21.00000 original
#> 99 12 F09 22.00000 original
#> 100 14 F09 21.50000 original
#> 101 8 F10 16.50000 original
#> 102 10 F10 19.00000 original
#> 103 12 F10 19.00000 original
#> 104 14 F10 19.50000 original
#> 105 8 F11 24.50000 original
#> 106 10 F11 25.00000 original
#> 107 12 F11 28.00000 original
#> 108 14 F11 28.00000 original
#> 109 8 M01 24.84572 fm1
#> 110 14 M01 30.03802 fm1
#> 111 8 M02 21.27478 fm1
#> 112 14 M02 25.83966 fm1
#> 113 8 M03 22.03311 fm1
#> 114 14 M03 26.62726 fm1
#> 115 8 M04 24.46452 fm1
#> 116 14 M04 28.32495 fm1
#> 117 8 M05 20.90249 fm1
#> 118 14 M05 25.55790 fm1
#> 119 8 M06 23.88527 fm1
#> 120 14 M06 28.52762 fm1
#> 121 8 M07 21.57351 fm1
#> 122 14 M07 26.20819 fm1
#> 123 8 M08 21.99187 fm1
#> 124 14 M08 25.95500 fm1
#> 125 8 M09 22.60752 fm1
#> 126 14 M09 27.63182 fm1
#> 127 8 M10 26.47272 fm1
#> 128 14 M10 31.48306 fm1
#> 129 8 M11 21.81724 fm1
#> 130 14 M11 25.68038 fm1
#> 131 8 M12 21.84919 fm1
#> 132 14 M12 26.84421 fm1
#> 133 8 M13 21.15031 fm1
#> 134 14 M13 27.66861 fm1
#> 135 8 M14 22.72716 fm1
#> 136 14 M14 27.01008 fm1
#> 137 8 M15 23.13140 fm1
#> 138 14 M15 28.45567 fm1
#> 139 8 M16 21.12319 fm1
#> 140 14 M16 25.29756 fm1
#> 141 8 F01 20.20973 fm1
#> 142 14 F01 22.81848 fm1
#> 143 8 F02 21.27124 fm1
#> 144 14 F02 24.69027 fm1
#> 145 8 F03 21.86869 fm1
#> 146 14 F03 25.42735 fm1
#> 147 8 F04 23.09591 fm1
#> 148 14 F04 26.14246 fm1
#> 149 8 F05 21.34035 fm1
#> 150 14 F05 23.88784 fm1
#> 151 8 F06 19.99832 fm1
#> 152 14 F06 22.58725 fm1
#> 153 8 F07 21.45516 fm1
#> 154 14 F07 24.47333 fm1
#> 155 8 F08 22.04815 fm1
#> 156 14 F08 24.49475 fm1
#> 157 8 F09 20.07189 fm1
#> 158 14 F09 22.50047 fm1
#> 159 8 F10 17.72334 fm1
#> 160 14 F10 20.22443 fm1
#> 161 8 F11 24.21723 fm1
#> 162 14 F11 27.70339 fm1
#> 1091 8 M01 24.81965 fm2
#> 1101 14 M01 30.07487 fm2
#> 1111 8 M02 21.43115 fm2
#> 1121 14 M02 25.47931 fm2
#> 1131 8 M03 22.15551 fm2
#> 1141 14 M03 26.33173 fm2
#> 1151 8 M04 24.51597 fm2
#> 1161 14 M04 28.08177 fm2
#> 1171 8 M05 21.07073 fm2
#> 1181 14 M05 25.18544 fm2
#> 1191 8 M06 23.92577 fm2
#> 1201 14 M06 28.38602 fm2
#> 1211 8 M07 21.71382 fm2
#> 1221 14 M07 25.88433 fm2
#> 1231 8 M08 22.14500 fm2
#> 1241 14 M08 25.53769 fm2
#> 1251 8 M09 22.68547 fm2
#> 1261 14 M09 27.46203 fm2
#> 1271 8 M10 26.38500 fm2
#> 1281 14 M10 31.61299 fm2
#> 1291 8 M11 21.98248 fm2
#> 1301 14 M11 25.23063 fm2
#> 1311 8 M12 21.96111 fm2
#> 1321 14 M12 26.60961 fm2
#> 1331 8 M13 21.22240 fm2
#> 1341 14 M13 27.66552 fm2
#> 1351 8 M14 22.83398 fm2
#> 1361 14 M14 26.71037 fm2
#> 1371 8 M15 23.17304 fm2
#> 1381 14 M15 28.38322 fm2
#> 1391 8 M16 21.30401 fm2
#> 1401 14 M16 24.85199 fm2
#> 1411 8 F01 20.13096 fm2
#> 1421 14 F01 23.02281 fm2
#> 1431 8 F02 21.10961 fm2
#> 1441 14 F02 25.12987 fm2
#> 1451 8 F03 21.67494 fm2
#> 1461 14 F03 25.93991 fm2
#> 1471 8 F04 22.87286 fm2
#> 1481 14 F04 26.65480 fm2
#> 1491 8 F05 21.21574 fm2
#> 1501 14 F05 24.16910 fm2
#> 1511 8 F06 19.92955 fm2
#> 1521 14 F06 22.77132 fm2
#> 1531 8 F07 21.30401 fm2
#> 1541 14 F07 24.85199 fm2
#> 1551 8 F08 21.89771 fm2
#> 1561 14 F08 24.81242 fm2
#> 1571 8 F09 20.00731 fm2
#> 1581 14 F09 22.66017 fm2
#> 1591 8 F10 17.75649 fm2
#> 1601 14 F10 20.21405 fm2
#> 1611 8 F11 23.92577 fm2
#> 1621 14 F11 28.38602 fm2