Hi everyone. I am really struggling to get done my analysis. I am just having problems with every line of code. Lately I have begun to mistrust the group_by function. A little piece of my code
sample<-structure(list(paciente = structure(c(6363, 6052, 6519, 6371,
6555, 6185, 6002, 6155, 6287, 6217), format.spss = "F5.0"), sexo_s1 = structure(c(1L,
2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L), .Label = c("Hombre", "Mujer"
), label = "Sexo", class = "factor"), edad_s1 = structure(c(66,
63, 72, 64, 72, 64, 70, 73, 63, 65), label = "Edad", format.spss = "F3.0"),
peso1_v00 = structure(c(84.4, 76.2, 88.3, 122, 72, 86.4,
78, 79, 65.5, 98.8), label = "Peso: 1a determinación", format.spss = "F5.1"),
cintura1_v00 = structure(c(104.5, 101, 107.5, 128.5, 107,
109.5, 105.5, 109, 97, 118.5), label = "Cintura: 1a determinación", format.spss = "F5.1"),
tasis2_e_v00 = structure(c(155, 131, 148, 147, 136, 154,
130, 154, 147, 139), label = "TA: tensión arterial 2: sistólica", format.spss = "F4.0"),
tadias2_e_v00 = structure(c(98, 76, 83, 84, 73, 80, 64, 80,
82, 78), label = "TA: tensión arterial 2: diastólica", format.spss = "F4.0"),
p17_total_v00 = structure(c(10, 8, 10, 10, 10, 5, 11, 9,
8, 5), label = "Cuestionario de 17 puntos: Suma de puntuación de P17", format.spss = "F3.0"),
geaf_tot_v00 = structure(c(1048.95, 4195.8, 4615.38, 3356.64,
839.16, 1608.39, 2958.04, 10209.79, 4335.66, 157.34), label = "AF: Gasto energético en actividad física total (MET•min/sem)", format.spss = "F8.2"),
glucosa_v00 = structure(c(97, 122, 109, 201, 143, 139, 95,
110, 101, 181), label = "Analítica: Glucosa en mg/dL", format.spss = "F4.0"),
albumi_v00 = structure(c(4.61, 4.52, 4.44, 4.48, 4.75, 4.87,
4.66, 4.86, 4.75, 4.99), label = "Analítica: Albúmina en g/dL", format.spss = "F6.2"),
coltot_v00 = structure(c(221, 218, 130, 261, 190, 221, 199,
185, 233, 232), label = "Analítica: Colesterol total en mg/dL", format.spss = "F4.0"),
hdl_v00 = structure(c(52, 54, 43, 42, 50, 67, 90, 50, 43,
51), label = "Analítica: Colesterol HDL en mg/dL", format.spss = "F4.0"),
ldl_calc_v00 = structure(c(148, 135, 75, 173, 128, 133, 84,
109, 134, 144), label = "Analítica: LDL calculado en mg/dL si trigli<=300", format.spss = "F4.0"),
trigli_v00 = structure(c(103, 144, 58, 232, 60, 106, 126,
131, 282, 186), label = "Analítica: Triglicéridos en mg/dL", format.spss = "F5.0"),
hba1c_v00 = structure(c(5.87, NA, 5.76, 7.98, 6.38, 7.01,
NA, 6.51, 5.95, 9.01), label = "Analítica: Hemoglobina glicosilada (HbA1c %)", format.spss = "F5.2"),
peso1_v66 = structure(c(76.6, 74.2, 82.2, 115, 64, 73.5,
74.4, 75.5, 59.5, 100), label = "Peso: 1a determinación", format.spss = "F5.1"),
cintura1_v66 = structure(c(97.5, 99, 100, 122.5, 99, 101,
97, 104.5, 82.5, 119.5), label = "Cintura: 1a determinación", format.spss = "F5.1"),
tasis2_e_v66 = structure(c(133, 129, 144, 160, 122, 123,
130, 155, 139, 153), label = "TA: tensión arterial 2: sistólica", format.spss = "F4.0"),
tadias2_e_v66 = structure(c(87, 75, 77, 86, 68, 53, 64, 81,
73, 89), label = "TA: tensión arterial 2: diastólica", format.spss = "F4.0", display_width = 13L),
p17_total_v66 = structure(c(12, 12, 12, 13, 11, 15, 14, 9,
15, 12), label = "Cuestionario de 17 puntos: Suma total de P17", format.spss = "F3.0"),
geaf_tot_v66 = structure(c(4615.38, 0, 3461.54, 3356.64,
2097.9, 5132.87, 5118.88, 8111.89, 6772.03, 209.79), label = "AF: Gasto energético en actividad física total (MET•min/sem)", format.spss = "F8.2"),
glucosa_v66 = structure(c(96, 107, 111, 173, 107, 98, 88,
118, 97, 185), label = "Analítica: Glucosa en mg/dL", format.spss = "F4.0"),
albumi_v66 = structure(c(4.5, 4.93, 4.41, 4.42, 4.82, 4.54,
4.8, 4.46, 4.64, 4.84), label = "Analítica: Albúmina en g/dL", format.spss = "F6.2"),
coltot_v66 = structure(c(215, 226, 156, 235, 154, 210, 283,
182, 225, 171), label = "Analítica: Colesterol total en mg/dL", format.spss = "F4.0"),
hdl_v66 = structure(c(54, 65, 54, 40, 51, 73, 88, 58, 46,
37), label = "Analítica: Colesterol HDL en mg/dL", format.spss = "F4.0"),
ldl_calc_v66 = structure(c(147, 133, 89, 156, 94, 123, 175,
106, 137, 102), label = "Analítica: LDL calculado en mg/dL si trigli<=300", format.spss = "F4.0"),
trigli_v66 = structure(c(72, 138, 63, 197, 47, 72, 99, 89,
209, 160), label = "Analítica: Triglicéridos en mg/dL", format.spss = "F5.0"),
hba1c_v66 = structure(c(5.67, NA, 5.54, 8.05, 5.5, 5.95,
NA, 6.17, 5.75, 8.98), label = "Analítica: Hemoglobina glicosilada (HbA1c %)", format.spss = "F5.2"),
peso1_v01 = structure(c(75.2, 72, 82.4, 116, 63, 73.5, 72.4,
79, 58.5, 100), label = "Peso: 1a determinación", format.spss = "F5.1"),
cintura1_v01 = structure(c(97.5, 98, 100, 122.5, 99, 101,
96, 106, 88.5, 119.5), label = "Cintura: 1a determinación", format.spss = "F5.1"),
tasis2_e_v01 = structure(c(130, 137, 137, 183, 122, 152,
138, 139, 147, 154), label = "TA: tensión arterial 2: sistólica", format.spss = "F4.0"),
tadias2_e_v01 = structure(c(84, 75, 72, 97, 71, 63, 72, 72,
60, 80), label = "TA: tensión arterial 2: diastólica", format.spss = "F4.0"),
p17_total_v01 = structure(c(14, 11, 12, 10, 14, 15, 14, 11,
13, 12), label = "Cuestionario de 17 puntos: Suma total de P17", format.spss = "F3.0"),
geaf_tot_v01 = structure(c(1678.32, 0, 4713.29, 559.44, 2769.23,
3212.12, 6853.15, 3776.22, 5841.49, 1048.95), label = "AF: Gasto energético en actividad física total (MET•min/sem)", format.spss = "F8.2"),
glucosa_v01 = structure(c(93, 116, 100, 200, 112, 109, 105,
118, 94, 242), label = "Analítica: Glucosa en mg/dL", format.spss = "F4.0"),
albumi_v01 = structure(c(4.57, 4.42, 4.68, 4.36, 4.98, 4.74,
4.87, 4.8, 4.81, 4.88), label = "Analítica: Albúmina en g/dL", format.spss = "F6.2"),
coltot_v01 = structure(c(198, 236, 158, 270, 181, 187, 213,
204, 226, 192), label = "Analítica: Colesterol total en mg/dL", format.spss = "F4.0"),
hdl_v01 = structure(c(58, 59, 48, 74, 60, 60, 87, 52, 49,
37), label = "Analítica: Colesterol HDL en mg/dL", format.spss = "F4.0"),
ldl_calc_v01 = structure(c(128, 160, 99, 168, 107, 109, 105,
130, 147, 125), label = "Analítica: LDL calculado en mg/dL si trigli<=300", format.spss = "F4.0"),
trigli_v01 = structure(c(62, 83, 53, 139, 71, 90, 105, 110,
148, 151), label = "Analítica: Triglicéridos en mg/dL", format.spss = "F5.0"),
hba1c_v01 = structure(c(5.61, 6.48, 5.53, 8.26, 5.86, 6.4,
5.26, 6.5, 5.7, 9.62), label = "Analítica: Hemoglobina glicosilada (HbA1c %)", format.spss = "F5.2"),
i_hucpeptide_v00 = structure(c(704.96, NA, 675.43, 913.16,
1325.4, 840.98, NA, 1932.23, 459.83, 422.15), label = "Hu C-peptide (72) IMIM S'han substituit en les següents var els codis de inf i sup a limit de detecció per el limit inf i sup de detecció", format.spss = "F9.2", display_width = 13L),
i_hucpeptide_v66 = structure(c(510.07, NA, 824.39, 926.34,
1199.51, 488.01, NA, 1461.11, 346.92, 679.09), label = "Hu C-peptide (72) IMIM", format.spss = "F9.2", display_width = 13L),
i_hucpeptide_v01 = structure(c(432.38, NA, 737.66, 707.55,
1057.83, 699.08, NA, 1512.69, 345.69, 356.67), label = "Hu C-peptide (72) IMIM", format.spss = "F9.2", display_width = 12L),
i_hughrelin_v00 = structure(c(1823.83, NA, 1050.11, 424.25,
198.06, 534.27, NA, 709.73, 117.69, 420.37), label = "Hu Ghrelin (26) IMIM", format.spss = "F7.2", display_width = 10L),
i_hughrelin_v66 = structure(c(1407.04, NA, 746.93, 423.13,
207.63, 464.17, NA, 728.57, 113.23, 463.65), label = "Hu Ghrelin (26) IMIM", format.spss = "F7.2", display_width = 13L),
i_hughrelin_v01 = structure(c(1133.96, NA, 670.23, 405.11,
260.24, 418.79, NA, 533.78, 122.07, 220.22), label = "Hu Ghrelin (26) IMIM", format.spss = "F7.2", display_width = 11L),
i_hugip_v00 = structure(c(2.67, NA, 2.67, 2.67, 2.67, 2.67,
NA, 2.67, 2.67, 2.67), label = "Hu GIP (14) IMIM", format.spss = "F9.2", display_width = 9L),
i_hugip_v66 = structure(c(2.67, NA, 2.67, 2.67, 256.21, 2.67,
NA, 2.67, 2.67, 2.67), label = "Hu GIP (14) IMIM", format.spss = "F9.2", display_width = 9L),
i_hugip_v01 = structure(c(2.67, NA, 2.67, 24.74, 1165.16,
2.67, NA, 2.67, 2.67, 2.67), label = "Hu GIP (14) IMIM", format.spss = "F9.2", display_width = 9L),
i_huglp1_v00 = structure(c(14.14, NA, 14.14, 216.2, 116.16,
228.14, NA, 359.48, 14.14, 219.02), label = "Hu GLP-1 (27) IMIM", format.spss = "F9.2", display_width = 9L),
i_huglp1_v66 = structure(c(14.14, NA, 14.14, 202.5, 92.49,
278.55, NA, 400.16, 14.14, 274.62), label = "Hu GLP-1 (27) IMIM", format.spss = "F9.2", display_width = 9L),
i_huglp1_v01 = structure(c(14.14, NA, 14.14, 202.5, 56.41,
303.77, NA, 451.91, 14.14, 58.55), label = "Hu GLP-1 (27) IMIM", format.spss = "F9.2", display_width = 9L),
i_huglucagon_v00 = structure(c(273.5, NA, 231.41, 491.4,
542.39, 489.35, NA, 525.39, 241.55, 362.72), label = "Hu Glucagon (15) IMIM", format.spss = "F9.2", display_width = 11L),
i_huglucagon_v66 = structure(c(94.97, NA, 276.26, 456.39,
306.42, 288.62, NA, 523.49, 143.14, 440.22), label = "Hu Glucagon (15) IMIM", format.spss = "F9.2", display_width = 11L),
i_huglucagon_v01 = structure(c(182.57, NA, 233.95, 522.65,
10.48, 409.99, NA, 511.95, 216.47, 326.51), label = "Hu Glucagon (15) IMIM", format.spss = "F9.2", display_width = 9L),
i_huinsulin_v00 = structure(c(97.94, NA, 171.33, 286.66,
390.29, 221.06, NA, 668.14, 125.36, 349.99), label = "Hu Insulin (12) IMIM", format.spss = "F7.2", display_width = 10L),
i_huinsulin_v66 = structure(c(64.73, NA, 236.01, 255.05,
284.71, 73.24, NA, 392.19, 64.75, 381.42), label = "Hu Insulin (12) IMIM", format.spss = "F7.2", display_width = 9L),
i_huinsulin_v01 = structure(c(52.52, NA, 213.4, 703.51, 247.48,
147.22, NA, 521.07, 98.66, 298.72), label = "Hu Insulin (12) IMIM", format.spss = "F7.2"),
i_huleptin_v00 = structure(c(3493.7, NA, 1965.55, 4767.39,
5122.91, 12320.55, NA, 5367.22, 5217.35, 4682.33), label = "Hu Leptin (78) IMIM", format.spss = "F9.2", display_width = 9L),
i_huleptin_v66 = structure(c(1779.33, NA, 1410.07, 3977.58,
3645.73, 3608.76, NA, 4489.67, 3499.88, 5136.43), label = "Hu Leptin (78) IMIM", format.spss = "F9.2", display_width = 9L),
i_huleptin_v01 = structure(c(1865.4, NA, 1312.5, 8371.63,
2128.98, 6921.89, NA, 3754.42, 3092.53, 3921.64), label = "Hu Leptin (78) IMIM", format.spss = "F9.2", display_width = 9L),
i_hupai1_v00 = structure(c(1581.8, NA, 1442.88, 3209.36,
2349.08, 3202.1, NA, 3177.94, 1463.04, 1701.4), label = "Hu PAI-1 (61) IMIM", format.spss = "F7.2"),
i_hupai1_v66 = structure(c(1625.45, NA, 1093.24, 2152.24,
2083.31, 982.35, NA, 2245.81, 1611.27, 2645.45), label = "Hu PAI-1 (61) IMIM", format.spss = "F7.2"),
i_hupai1_v01 = structure(c(1726.35, NA, 1166.53, 2511.45,
2268.52, 1592.08, NA, 2560.71, 1936.33, 2500.51), label = "Hu PAI-1 (61) IMIM", format.spss = "F7.2"),
i_huresistin_v00 = structure(c(4292.62, NA, 3951.76, 4101.48,
6430.17, 5599.94, NA, 4855.32, 2144.19, 2421.1), label = "Hu Resistin (65) IMIM", format.spss = "F8.2", display_width = 9L),
i_huresistin_v66 = structure(c(3201.72, NA, 4774.83, 4500.78,
7574.37, 4403.32, NA, 3224.09, 2102.65, 2003.5), label = "Hu Resistin (65) IMIM", format.spss = "F8.2", display_width = 7L),
i_huresistin_v01 = structure(c(3872.84, NA, 4595.27, 3581.62,
9521.7, 4225.4, NA, 3150.62, 2093.1, 2048.76), label = "Hu Resistin (65) IMIM", format.spss = "F8.2", display_width = 6L),
i_huvisfatin_v00 = structure(c(8.64, NA, 2.06, 560.32, 1498.58,
1356.01, NA, 632.07, 315.62, 461.86), label = "Hu Visfatin (22) IMIM", format.spss = "F9.2", display_width = 6L),
i_huvisfatin_v66 = structure(c(8.64, NA, 8.64, 472.64, 683.91,
8.64, NA, 486.94, 8.64, 477.56), label = "Hu Visfatin (22) IMIM", format.spss = "F9.2", display_width = 6L),
i_huvisfatin_v01 = structure(c(8.64, NA, 8.64, 2113.05, 1415.55,
800.08, NA, 155.08, 8.64, 108), label = "Hu Visfatin (22) IMIM", format.spss = "F9.2", display_width = 10L),
col_rema_v00 = structure(c(21, 29, 12, 46, 12, 21, 25, 26,
56, 37), format.spss = "F8.2", display_width = 14L), col_rema_v66 = structure(c(14,
28, 13, 39, 9, 14, 20, 18, 42, 32), format.spss = "F8.2", display_width = 14L),
col_rema_v01 = structure(c(12, 17, 11, 28, 14, 18, 21, 22,
30, 30), format.spss = "F8.2", display_width = 14L), homa_v00 = structure(c(422.230222222222,
NA, 829.998666666667, 2560.82933333333, 2480.50977777778,
1365.65955555556, NA, 3266.46222222222, 562.727111111111,
2815.47511111111), format.spss = "F8.2", display_width = 10L),
homa_v66 = structure(c(276.181333333333, NA, 1164.316, 1961.05111111111,
1353.95422222222, 319.000888888889, NA, 2056.81866666667,
279.144444444444, 3136.12), format.spss = "F8.2", display_width = 10L),
homa_v01 = structure(c(217.082666666667, NA, 948.444444444444,
6253.42222222222, 1231.90044444444, 713.199111111111, NA,
2732.72266666667, 412.179555555556, 3212.89955555556), format.spss = "F8.2", display_width = 10L),
d_homa_v66 = structure(c(-146.048888888889, NA, 334.317333333333,
-599.778222222222, -1126.55555555556, -1046.65866666667,
NA, -1209.64355555556, -283.582666666667, 320.644888888889
), format.spss = "F8.2", display_width = 12L), d_homa_v01 = structure(c(-205.147555555556,
NA, 118.445777777778, 3692.59288888889, -1248.60933333333,
-652.460444444444, NA, -533.739555555555, -150.547555555556,
397.424444444444), format.spss = "F8.2", display_width = 12L),
d_hughrelin_v66 = structure(c(-416.79, NA, -303.18, -1.12,
9.56999999999999, -70.1, NA, 18.84, -4.45999999999999, 43.28
), format.spss = "F8.2", display_width = 18L), d_hughrelin_v01 = structure(c(-689.87,
NA, -379.88, -19.14, 62.18, -115.48, NA, -175.95, 4.38, -200.15
), format.spss = "F8.2", display_width = 18L), d_huinsulin_v66 = structure(c(-33.21,
NA, 64.68, -31.61, -105.58, -147.82, NA, -275.95, -60.61,
31.43), format.spss = "F8.2", display_width = 17L), d_huinsulin_v01 = structure(c(-45.42,
NA, 42.07, 416.85, -142.81, -73.84, NA, -147.07, -26.7, -51.27
), format.spss = "F8.2", display_width = 17L), d_hucpeptide_v66 = structure(c(-194.89,
NA, 148.96, 13.1800000000001, -125.89, -352.97, NA, -471.12,
-112.91, 256.94), format.spss = "F8.2", display_width = 18L),
d_hucpeptide_v01 = structure(c(-272.58, NA, 62.23, -205.61,
-267.57, -141.9, NA, -419.54, -114.14, -65.48), format.spss = "F8.2", display_width = 18L),
d_huglucagon_v66 = structure(c(-178.53, NA, 44.85, -35.01,
-235.97, -200.73, NA, -1.89999999999998, -98.41, 77.5), format.spss = "F8.2", display_width = 18L),
d_huglucagon_v01 = structure(c(-90.93, NA, 2.53999999999999,
31.25, -531.91, -79.36, NA, -13.44, -25.08, -36.21), format.spss = "F8.2", display_width = 18L),
d_huleptin_v66 = structure(c(-1714.37, NA, -555.48, -789.81,
-1477.18, -8711.79, NA, -877.55, -1717.47, 454.1), format.spss = "F8.2", display_width = 16L),
d_huleptin_v01 = structure(c(-1628.3, NA, -653.05, 3604.24,
-2993.93, -5398.66, NA, -1612.8, -2124.82, -760.69), format.spss = "F8.2", display_width = 16L),
d_huresistin_v66 = structure(c(-1090.9, NA, 823.07, 399.3,
1144.2, -1196.62, NA, -1631.23, -41.54, -417.6), format.spss = "F8.2", display_width = 18L),
d_huresistin_v01 = structure(c(-419.78, NA, 643.51, -519.86,
3091.53, -1374.54, NA, -1704.7, -51.0900000000001, -372.34
), format.spss = "F8.2", display_width = 18L), d_huvisfatin_v66 = structure(c(0,
NA, 6.58, -87.6800000000001, -814.67, -1347.37, NA, -145.13,
-306.98, 15.7), format.spss = "F8.2", display_width = 18L),
d_huvisfatin_v01 = structure(c(0, NA, 6.58, 1552.73, -83.03,
-555.93, NA, -476.99, -306.98, -353.86), format.spss = "F8.2", display_width = 18L),
d_glucosa_v66 = structure(c(-1, -15, 2, -28, -36, -41, -7,
8, -4, 4), format.spss = "F8.2", display_width = 15L), d_glucosa_v01 = structure(c(-4,
-6, -9, -1, -31, -30, 10, 8, -7, 61), format.spss = "F8.2", display_width = 15L),
d_coltot_v66 = structure(c(-6, 8, 26, -26, -36, -11, 84,
-3, -8, -61), format.spss = "F8.2", display_width = 14L),
d_coltot_v01 = structure(c(-23, 18, 28, 9, -9, -34, 14, 19,
-7, -40), format.spss = "F8.2", display_width = 14L), d_hdl_v66 = structure(c(2,
11, 11, -2, 1, 6, -2, 8, 3, -14), format.spss = "F8.2", display_width = 11L),
d_hdl_v01 = structure(c(6, 5, 5, 32, 10, -7, -3, 2, 6, -14
), format.spss = "F8.2", display_width = 11L), d_ldl_calc_v66 = structure(c(-1,
-2, 14, -17, -34, -10, 91, -3, 3, -42), format.spss = "F8.2", display_width = 16L),
d_ldl_calc_v01 = structure(c(-20, 25, 24, -5, -21, -24, 21,
21, 13, -19), format.spss = "F8.2", display_width = 16L),
d_col_rema_v66 = structure(c(-7, -1, 1, -7, -3, -7, -5, -8,
-14, -5), format.spss = "F8.2", display_width = 16L), d_col_rema_v01 = structure(c(-9,
-12, -1, -18, 2, -3, -4, -4, -26, -7), format.spss = "F8.2", display_width = 16L),
d_trigli_v66 = structure(c(-31, -6, 5, -35, -13, -34, -27,
-42, -73, -26), format.spss = "F8.2", display_width = 14L),
d_trigli_v01 = structure(c(-41, -61, -5, -93, 11, -16, -21,
-21, -134, -35), format.spss = "F8.2", display_width = 14L),
d_hba1c_v66 = structure(c(-0.2, NA, -0.22, 0.0700000000000003,
-0.88, -1.06, NA, -0.34, -0.2, -0.0299999999999994), format.spss = "F8.2", display_width = 13L),
d_hba1c_v01 = structure(c(-0.26, NA, -0.23, 0.279999999999999,
-0.52, -0.609999999999999, NA, -0.00999999999999979, -0.25,
0.609999999999999), format.spss = "F8.2", display_width = 13L),
d_tasis2_e_v66 = structure(c(-22, -2, -4, 13, -14, -31, 0,
1, -8, 14), format.spss = "F8.2", display_width = 16L), d_tasis2_e_v01 = structure(c(-25,
6, -11, 36, -14, -2, 8, -15, 0, 15), format.spss = "F8.2", display_width = 16L),
d_tadias2_e_v66 = structure(c(-11, -1, -6, 2, -5, -27, 0,
1, -9, 11), format.spss = "F8.2", display_width = 17L), d_tadias2_e_v01 = structure(c(-14,
-1, -11, 13, -2, -17, 8, -8, -22, 2), format.spss = "F8.2", display_width = 17L),
d_peso1_v66 = structure(c(-7.80000000000001, -2, -6.09999999999999,
-7, -8, -12.9, -3.59999999999999, -3.5, -6, 1.2), format.spss = "F8.2", display_width = 13L),
d_peso1_v01 = structure(c(-9.2, -4.2, -5.89999999999999,
-6, -9, -12.9, -5.59999999999999, 0, -7, 1.2), format.spss = "F8.2", display_width = 13L),
d_cintura1_v66 = structure(c(-7, -2, -7.5, -6, -8, -8.5,
-8.5, -4.5, -14.5, 1), format.spss = "F8.2", display_width = 16L),
d_cintura1_v01 = structure(c(-7, -3, -7.5, -6, -8, -8.5,
-9.5, -3, -8.5, 1), format.spss = "F8.2", display_width = 16L),
d_geaf_tot_v66 = structure(c(3566.43, -4195.8, -1153.84,
0, 1258.74, 3524.48, 2160.84, -2097.9, 2436.37, 52.45), format.spss = "F8.2", display_width = 16L),
d_geaf_tot_v01 = structure(c(629.37, -4195.8, 97.9099999999999,
-2797.2, 1930.07, 1603.73, 3895.11, -6433.57, 1505.83, 891.61
), format.spss = "F8.2", display_width = 16L), d_p17_total_v66 = structure(c(2,
4, 2, 3, 1, 10, 3, 0, 7, 7), format.spss = "F8.2", display_width = 11L),
d_p17_total_v01 = structure(c(4, 3, 2, 0, 4, 10, 3, 2, 5,
7), format.spss = "F8.2"), d_hupai1_v66 = structure(c(43.6500000000001,
NA, -349.64, -1057.12, -265.77, -2219.75, NA, -932.13, 148.23,
944.05), format.spss = "F8.2", display_width = 13L), d_hupai1_v01 = structure(c(144.55,
NA, -276.35, -697.91, -80.5599999999999, -1610.02, NA, -617.23,
473.29, 799.11), format.spss = "F8.2", display_width = 13L),
d_hugip_v66 = structure(c(0, NA, 0, 0, 253.54, 0, NA, 0,
0, 0), format.spss = "F8.2", display_width = 13L), d_hugip_v01 = structure(c(0,
NA, 0, 22.07, 1162.49, 0, NA, 0, 0, 0), format.spss = "F8.2", display_width = 13L),
d_huglp1_v66 = structure(c(0, NA, 0, -13.7, -23.67, 50.41,
NA, 40.68, 0, 55.6), format.spss = "F8.2", display_width = 13L),
d_huglp1_v01 = structure(c(0, NA, 0, -13.7, -59.75, 75.63,
NA, 92.43, 0, -160.47), format.spss = "F8.2", display_width = 13L),
ln_trigli_v00 = structure(c(4.63472898822964, 4.969813299576,
4.06044301054642, 5.44673737166631, 4.0943445622221, 4.66343909411207,
4.83628190695148, 4.87519732320115, 5.64190707093811, 5.2257466737132
), label = "Analítica: Triglicéridos en mg/dL", format.spss = "F5.0"),
ln_trigli_v66 = structure(c(4.27666611901606, 4.92725368515721,
4.14313472639153, 5.28320372873799, 3.85014760171006, 4.27666611901606,
4.59511985013459, 4.48863636973214, 5.34233425196481, 5.07517381523383
), label = "Analítica: Triglicéridos en mg/dL", format.spss = "F5.0"),
ln_trigli_v01 = structure(c(4.12713438504509, 4.4188406077966,
3.97029191355212, 4.93447393313069, 4.26267987704132, 4.49980967033027,
4.65396035015752, 4.70048036579242, 4.99721227376411, 5.01727983681492
), label = "Analítica: Triglicéridos en mg/dL", format.spss = "F5.0"),
ln_homa_v00 = structure(c(6.04555071556718, NA, 6.72142409436365,
7.84808644334377, 7.81621937359094, 7.21939278180313, NA,
8.09146278899802, 6.33279480567865, 7.94288630470217), format.spss = "F8.2", display_width = 10L),
ln_homa_v66 = structure(c(5.62105765481488, NA, 7.05988906911122,
7.58123588965634, 7.21078464361132, 5.76519388926651, NA,
7.62891573149717, 5.63172936987266, 8.05074164604432), format.spss = "F8.2", display_width = 10L),
ln_homa_v01 = structure(c(5.38027823337748, NA, 6.85482321564537,
8.74088414843216, 7.11631333274751, 6.56976063964933, NA,
7.91305370498932, 6.02145906886522, 8.07492909673972), format.spss = "F8.2", display_width = 10L),
ln_hba1c_v00 = structure(c(1.76985463384001, NA, 1.7509374747078,
2.07693841146172, 1.8531680973567, 1.9473377010465, NA, 1.87333945622048,
1.78339121955754, 2.19833507162025), label = "Analítica: Hemoglobina glicosilada (HbA1c %)", format.spss = "F5.2"),
ln_hba1c_v66 = structure(c(1.73518911773966, NA, 1.71199450075919,
2.08567209143047, 1.70474809223843, 1.78339121955754, NA,
1.8196988379173, 1.74919985480926, 2.19499988231411), label = "Analítica: Hemoglobina glicosilada (HbA1c %)", format.spss = "F5.2"),
ln_hba1c_v01 = structure(c(1.72455071953461, 1.86872051036418,
1.71018781553424, 2.11142458753289, 1.76814960358892, 1.85629799036563,
1.66013102674962, 1.87180217690159, 1.7404661748405, 2.26384426467762
), label = "Analítica: Hemoglobina glicosilada (HbA1c %)", format.spss = "F5.2"),
ln_geaf_tot_v00 = structure(c(6.95554494281799, 8.34183930393788,
8.4371494837422, 8.11869575262367, 6.73240139150378, 7.38298895764493,
7.99228216582975, 9.23110234287667, 8.37462912676087, 5.0584090689011
), label = "AF: Gasto energético en actividad física total (MET•min/sem)", format.spss = "F8.2"),
ln_geaf_tot_v66 = structure(c(8.4371494837422, -Inf, 8.14946885573527,
8.11869575262367, 7.64869212337793, 8.5434202359197, 8.54069094410428,
9.00108616558123, 8.82055617324912, 5.34610703038388), label = "AF: Gasto energético en actividad física total (MET•min/sem)", format.spss = "F8.2"),
ln_geaf_tot_v01 = structure(c(7.42554857206372, -Inf, 8.45814145696367,
6.32693628339561, 7.92632458219889, 8.07468643426916, 8.83246367957041,
8.23647878828005, 8.67274118026667, 6.95554494281799), label = "AF: Gasto energético en actividad física total (MET•min/sem)", format.spss = "F8.2")), row.names = c(NA,
-10L), class = c("tbl_df", "tbl", "data.frame"))
Then it comes a little bit of data wrangling before the t.test operations. I have taken 2 pathways to perform the analysis and confirm if it is working the group_by function. Confirm my method is what I want. The long way to confirm my operations. I subset the database a previous step to filter individually the variables
s_sample <-s_sample<-sample %>%
dplyr::select(paciente, matches(c("_v00", "_v01", "_v66"))) %>%
mutate(terciles_d_coltot_v66 = ntile(.$d_coltot_v66,3)) %>%
dplyr::select(paciente, matches("_v66")) %>%
pivot_longer(!c(paciente, terciles_d_coltot_v66)) %>%
dplyr::filter(terciles_d_coltot_v66 == "1" | terciles_d_coltot_v66 == "2") %>%
mutate(terciles_d_coltot_v66 = factor(terciles_d_coltot_v66)) %>%
pivot_wider(names_from= terciles_d_coltot_v66, values_from=value) %>%
select(-paciente) %>%
group_by(name)
After this I am picking variables individually
s_sample %>% filter(name=="tadias2_e_v66") %>% do(tidy(t.test(.$`2`, .$`1`, na.rm = TRUE)))
name estimate estimate1 estimate2 statistic p.value parameter conf.low conf.high method alternative
1 tadias2_e_v66 6.33 80.3 74 0.679 0.532 4.22 -19.0 31.7 Welch Two Sample t-test two.sided
Ok, this is the long-way code to confirm what I have done before. This is:
sample %>%
dplyr::select(paciente, matches(c("_v00", "_v01", "_v66"))) %>%
mutate(terciles_d_coltot_v66 = ntile(.$d_coltot_v66,3)) %>%
dplyr::select(paciente, matches("_v66")) %>%
pivot_longer(!c(paciente, terciles_d_coltot_v66)) %>%
dplyr::filter(terciles_d_coltot_v66 == "1" | terciles_d_coltot_v66 == "2") %>%
mutate(terciles_d_coltot_v66 = factor(terciles_d_coltot_v66)) %>%
pivot_wider(names_from= terciles_d_coltot_v66, values_from=value) %>%
select(-paciente) %>%
group_by(name) %>%
do(tidy(t.test(.$"1", .$"2", na.rm = TRUE)))
If you compare both results and repeat it with more variables you will see that something is happening there.
I am interested in pvalues but the thing is I don't get why the results don't match. Is the group_by function not grouping variables by name?? This function is supposed to do that?
Clarification: The 1 and 2 groups are terciles of one specific variable
Thanks in advance