I would like fit several mixed-effects spline models where the only difference between models is the degree of freedom (df) of the spline term (2 to 6 df). How can I automate this process and save the models in an object or list so that I can explore the BIC of each model.
This is the example data
library(nlme)
library(splines)
library(tidyverse)
data <- structure(list(id = c(1001L, 1001L, 1001L, 1001L, 1001L, 1002L,
1003L, 1004L, 1004L, 1004L, 1004L, 1004L, 1004L, 1004L, 1005L,
1005L, 1005L, 1005L, 1005L, 1006L, 1006L, 1006L, 1006L, 1006L,
1007L, 1007L, 1008L, 1008L, 1008L, 1008L, 1008L, 1009L, 1009L,
1009L, 1010L, 1010L, 1010L, 1011L, 1012L, 1012L, 1012L, 1013L,
1013L, 1014L, 1015L, 1015L, 1015L, 1016L, 1016L, 1016L, 1016L,
1016L, 1017L, 1017L, 1018L, 1020L, 1020L, 1021L, 1021L, 1021L,
1021L, 1022L, 1022L, 1023L, 1023L, 1023L, 1023L, 1023L, 1023L,
1023L, 1023L, 1023L, 1023L, 1024L, 1024L, 1024L, 1024L, 1024L,
1025L, 1025L, 1025L, 1026L, 1026L, 1026L, 1026L, 1027L, 1027L,
1028L, 1028L, 1028L, 1028L, 1028L, 1028L, 1028L, 1029L, 1029L,
1029L, 1029L, 1029L, 1029L, 1030L, 1030L, 1030L, 1030L, 1030L,
1030L, 1030L, 1030L, 1031L, 1031L, 1031L, 1031L, 1032L, 1032L,
1032L, 1032L, 1032L, 1033L, 1033L, 1033L, 1033L, 1034L, 1034L,
1034L, 1034L, 1034L, 1035L, 1035L, 1036L, 1037L, 1037L, 1037L,
1037L, 1039L, 1039L, 1040L, 1040L, 1040L, 1040L, 1040L, 1040L,
1041L, 1041L, 1041L, 1041L, 1041L, 1041L, 1042L, 1042L, 1042L,
1042L, 1042L, 1042L, 1042L, 1043L, 1043L, 1043L, 1043L, 1044L,
1044L, 1044L, 1045L, 1045L, 1045L, 1045L, 1045L, 1045L, 1047L,
1048L, 1048L, 1049L, 1049L, 1049L, 1049L, 1051L, 1051L, 1052L,
1052L, 1052L, 1052L, 1052L, 1053L, 1053L, 1053L, 1053L, 1053L,
1054L, 1054L, 1054L, 1054L, 1054L, 1054L, 1054L, 1054L, 1056L,
1056L, 1056L, 1056L, 1057L, 1057L, 1058L, 1058L, 1058L, 1058L,
1058L, 1060L, 1060L, 1060L, 1061L, 1061L, 1061L, 1061L, 1061L,
1062L, 1062L, 1062L, 1062L, 1062L, 1063L, 1063L, 1063L, 1064L,
1064L, 1064L, 1064L, 1065L, 1065L, 1066L, 1066L, 1066L, 1066L,
1066L, 1066L, 1067L, 1067L, 1067L, 1068L, 1068L, 1068L, 1068L,
1068L, 1068L, 1068L, 1069L, 1070L, 1070L, 1070L, 1071L, 1071L,
1071L, 1072L, 1072L, 1072L, 1072L, 1072L, 1073L, 1073L, 1073L,
1073L, 1074L, 1074L, 1074L, 1075L, 1075L, 1075L, 1075L, 1075L,
1075L, 1076L, 1076L, 1076L, 1077L, 1077L, 1077L, 1077L, 1077L,
1077L, 1078L, 1078L, 1078L, 1078L, 1078L, 1078L, 1078L, 1080L,
1080L, 1080L, 1080L, 1081L, 1081L, 1082L, 1082L, 1082L, 1083L,
1083L, 1084L, 1085L, 1085L, 1085L, 1085L, 1085L, 1085L, 1086L,
1086L, 1086L, 1087L, 1087L, 1087L, 1087L, 1087L, 1087L, 1087L,
1087L, 1088L, 1088L, 1088L, 1088L, 1089L, 1089L, 1089L, 1089L,
1089L, 1090L, 1090L, 1091L, 1091L, 1091L, 1091L, 1091L, 1092L,
1092L, 1092L, 1092L, 1092L, 1093L, 1093L, 1093L, 1093L, 1094L,
1094L, 1094L, 1094L, 1094L, 1095L, 1095L, 1095L, 1095L, 1096L,
1097L, 1097L, 1098L, 1098L, 1098L, 1098L, 1098L, 1099L, 1099L,
1099L, 1099L, 1099L, 1099L, 1099L, 1099L, 1100L, 1100L, 1100L,
1101L, 1101L, 1101L, 1101L, 1103L, 1103L, 1103L, 1103L, 1103L,
1103L, 1103L, 1104L, 1104L, 1104L, 1104L, 1105L, 1105L, 1105L,
1106L, 1106L, 1106L, 1106L, 1106L, 1106L, 1106L, 1106L, 1106L,
1107L, 1108L, 1110L, 1111L, 1112L, 1117L, 1123L), y = c(1934.047646,
1075.598345, 1956.214821, 2000.38538, 2000.38538, 732.315937,
3119.86, 624.951231, 791.2764892, 1884.530826, 624.951231, 1047.57,
1047.57, 791.2764892, 1238.306103, 1555.042976, 2547.870529,
2547.870529, 2467.385, 1181.635212, 1181.635212, 565.306282,
2016.027874, 2016.027874, 712.6134567, 635.2537841, 2167.362267,
2575.574188, 2167.362267, 2480.028259, 2575.574188, 2875.363243,
1180.139938, 2828.037147, 3017.119362, 2722.940933, 2167.92,
2409.652458, 2245.442558, 724.1520328, 635.6034756, 1649.08326,
966.8182507, 865.2717723, 1570.23, 916.1300105, 1180.999973,
2351.32885, 2418.851707, 2290.038887, 2224.060562, 2509.52, 1174.589081,
1540.219376, 2692.26, 1300.899734, 1100.650177, 1786.628242,
1705.842979, 543.8596134, 1786.628242, 2115.374241, 2331.46,
875.949604, 2241.945103, 2319.666939, 2316.220234, 719.7139549,
2042.803307, 719.7139549, 1132.977503, 875.949604, 2316.220234,
1737.18, 1351.629826, 1291.44593, 1291.44593, 1108.26586, 1028.979719,
1291.44593, 2068.934227, 2440.784416, 1036.72, 894.6663704, 2449.184731,
1109.9, 672.9310664, 2072.320354, 2114.215416, 2114.215416, 1805.422001,
2461.18, 2101.374248, 2105.879, 1600.086481, 2866.84, 1600.086481,
2807.311, 3055.569931, 1600.086481, 2602.287521, 2690.007614,
620.5975037, 2608.4, 2722.3, 2713.66185, 2608.4, 1590.002, 2198.211,
2488.097725, 2198.211, 2322.616348, 2627.1, 2418.328346, 2601.661034,
531.7369251, 811.9494571, 884.31, 768.0526981, 652.1271248, 768.0526981,
2767.479, 1047.144354, 1047.144354, 1995.119, 1995.119, 707.6093158,
707.6093158, 1120.650104, 3036.591904, 3036.591904, 3081.86,
1193.583691, 2056.569244, 1823.155, 1238.948124, 2124.685, 887.20438,
1823.155, 2056.569244, 2056.569244, 2560.155342, 3095.923164,
3095.923164, 3003.729011, 2861.12, 2560.155342, 2735.26, 822.8209591,
1648.951, 1648.951, 1648.951, 822.8209591, 906.7692623, 582.787096,
1286.45, 797.2365359, 2566.770554, 2666.41, 2666.41, 2045.320816,
2401.21, 2401.21, 2583.2, 2581.32, 2622.357, 2581.32, 2588.462498,
442.433671, 1251.627064, 406.2565479, 2108.787437, 983.1101169,
2102.085403, 1155.713411, 1909.797131, 2871.55, 2711.07, 2883.22245,
2883.22245, 2711.07, 3027.103172, 3108.21537, 3007.87294, 3208.963631,
3108.21537, 2617.91, 2457.464466, 2890.51, 2698.48214, 2700.723,
2700.723, 2817.668579, 2700.723, 1349.90691, 1476.19994, 1552.95,
1349.90691, 925.8325004, 1258.28, 840.1875095, 2405.175911, 840.1875095,
1056.678543, 1571.936, 1210.89, 1210.89, 673.7005405, 687.7842464,
1016.86, 1217.866, 1493.791817, 2246.726913, 1054.821, 1054.821,
563.6580887, 1054.821, 1540.429863, 2209.006493, 1437.835186,
2191.308, 1412.128944, 2724.164597, 2791.705185, 2727.774208,
2070.451198, 866.7974147, 1661.082638, 2108.271309, 2411.515434,
2342.026085, 2071.06, 2258.321014, 1537.06, 760.6319065, 867.7596569,
1907.60466, 1770.658, 760.6319065, 912.8781966, 912.8781966,
912.8781966, 1257.222706, 2586.922356, 1608.28, 962.5674305,
1085.451181, 2539.218132, 2535.526085, 2561.60054, 1600.198,
2100.048149, 758.3851737, 758.3851737, 2643.373329, 367.7795143,
866.0683727, 718.5049658, 866.0683727, 1906.694649, 2291.48,
2190.560314, 744.1710777, 1498.981777, 2460.912292, 590.1345787,
2487.559135, 1855.601353, 660.9104843, 1116.08, 792.929533, 708.8373737,
2272.232933, 1801.729801, 2299.800095, 2272.232933, 2299.800095,
1895.828438, 1757.75, 1050.279345, 1757.75, 1326.09478, 1326.09478,
1633.119305, 1558, 1167.971405, 1828.16, 1788.571758, 2175.469,
1071.039494, 941.6030864, 2053.067215, 1461.02132, 1597.646778,
1885.321567, 2195.704372, 2195.704372, 1675.768558, 3157.550789,
1565.173126, 2195.704372, 3157.550789, 2404.836883, 2541.045593,
585.7223682, 2465.177761, 2678.462074, 500.3733997, 2465.177761,
781.342, 898.3551559, 2465.177761, 2465.177761, 1807.02, 1418.888027,
1797.36, 1807.02, 2200.06, 2218.369926, 2200.06, 1986.642735,
2088.292, 2069.139, 1507.901432, 2061.395798, 2075.164864, 2081.913219,
2081.913219, 483.8579493, 1857.88, 2578.772636, 1857.88, 1857.88,
1039.632153, 2288.28, 2288.28, 1831.349922, 2349.23, 933.1002788,
2626.298935, 1521.744, 933.1002788, 2626.298935, 1984.760715,
2450.333, 1732.339031, 1984.760715, 2731.9, 869.2320918, 1785.72,
1922.798, 3081.28, 1508.8, 2421.288597, 1922.798, 1268.074959,
1569.05, 1808.115, 1569.05, 1268.074959, 2165.724808, 2165.724808,
1808.115, 2084.149837, 2693.027184, 2464.489, 2607.653496, 1012.837271,
1012.837271, 2673.190872, 2635.290516, 2773.42, 2635.290516,
2654.772674, 2377.905655, 2679.014969, 2654.772674, 1226.40016,
1470.69, 1273.789799, 2294.926086, 1226.40016, 1470.69, 1273.789799,
1873.817, 2274.930534, 2317.429165, 959.1709613, 1328.159428,
1328.159428, 1328.159428, 959.1709613, 1630.28, 1610.54982, 2507.05302,
750.467966, 750.467966, 821.2255058, 802.8240452, 2829.47879),
age = c(31.54004107, 11.95071869, 27.88501027, 27.88501027,
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294L, 340L, 20L, 75L, 86L, 165L, 167L, 47L, 89L, 298L, 318L,
211L, 350L, 380L, 66L, 79L, 90L, 234L, 309L, 61L, 99L, 139L,
276L, 299L, 344L, 348L, 361L, 313L, 337L, 379L, 9L, 58L, 181L,
187L, 17L, 100L, 121L, 123L, 184L, 206L, 220L, 178L, 292L, 386L,
392L, 194L, 252L, 272L, 3L, 56L, 134L, 136L, 183L, 216L, 246L,
296L, 363L, 169L, 388L, 78L, 34L, 13L, 91L, 317L), class = "data.frame")
The models I am fitting have the following form (here shown for a spline terms with 2 degrees of freedom):
lme(y ~ bs(age, degree = 1, df = 2), data = data, random = ~age|id, method = "ML")
This is what I have tried so far but unsuccessfully
df <- 2:6
spline_models <- map(setNames(df, df), ~{
. <- lme(y ~ bs(age, degree = 1, df = .x), data = data, random = ~age|id, method = "ML")
.
})
