R version 2.9.0 (2009-04-17) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. 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(j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Pearson Chi-Squared' > par2 = '2' > par1 = '1' > main = 'Association Plot' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(vcd) Loading required package: MASS Loading required package: grid Loading required package: colorspace > cat1 <- as.numeric(par1) # > cat2<- as.numeric(par2) # > simulate.p.value=FALSE > if (par3 == 'Exact Pearson Chi-Squared by Simulation') simulate.p.value=TRUE > x <- t(x) > (z <- array(unlist(x),dim=c(length(x[,1]),length(x[1,])))) [,1] [,2] [1,] 30 1 [2,] 5 1 [3,] 5 0 [4,] 30 0 [5,] 25 0 [6,] 50 1 [7,] 65 1 [8,] 40 0 [9,] 55 1 [10,] 75 0 [11,] 50 0 [12,] 20 1 [13,] 25 1 [14,] 30 1 [15,] 80 1 [16,] 0 25 [17,] 0 50 [18,] 1 35 [19,] 1 40 [20,] 0 40 [21,] 1 50 [22,] 1 30 [23,] 1 45 [24,] 1 30 [25,] 1 25 [26,] 0 25 [27,] 1 20 [28,] 1 35 [29,] 1 30 [30,] 1 45 [31,] 0 40 [32,] 1 30 [33,] 1 60 [34,] 1 45 [35,] 0 45 [36,] 1 25 [37,] 1 1 [38,] 45 0 [39,] 50 0 [40,] 0 45 [41,] 1 60 [42,] 1 60 [43,] 1 45 [44,] 1 45 [45,] 0 0 [46,] 45 1 [47,] 55 1 [48,] 40 1 [49,] 60 1 [50,] 35 0 [51,] 30 0 [52,] 20 0 [53,] 15 1 [54,] 15 1 [55,] 40 1 [56,] 40 1 [57,] 50 0 [58,] 1 40 [59,] 0 80 [60,] 1 50 [61,] 0 50 [62,] 1 30 [63,] 1 35 [64,] 1 40 [65,] 1 30 [66,] 1 45 [67,] 1 1 [68,] 0 30 [69,] 0 30 [70,] 1 25 [71,] 1 0 [72,] 50 0 [73,] 40 1 [74,] 40 0 [75,] 65 1 [76,] 55 1 [77,] 0 70 [78,] 0 40 [79,] 1 65 [80,] 1 40 [81,] 0 40 [82,] 1 55 [83,] 1 30 [84,] 1 35 [85,] 1 35 [86,] 0 30 [87,] 1 35 [88,] 1 20 [89,] 1 55 [90,] 1 5 [91,] 1 55 [92,] 1 50 [93,] 0 30 [94,] 1 50 [95,] 1 50 [96,] 1 50 [97,] 1 40 [98,] 0 25 [99,] 1 40 [100,] 1 55 [101,] 1 40 [102,] 0 0 [103,] 1 1 [104,] 40 1 [105,] 30 0 [106,] 25 1 [107,] 30 1 [108,] 25 1 [109,] 20 0 [110,] 65 0 [111,] 60 1 [112,] 30 1 [113,] 0 0 [114,] 50 1 [115,] 45 1 [116,] 1 25 [117,] 1 60 [118,] 1 50 [119,] 1 0 [120,] 40 0 [121,] 35 1 [122,] 50 0 [123,] 35 1 [124,] 25 1 [125,] 45 1 [126,] 25 0 [127,] 50 1 [128,] 1 75 [129,] 0 55 [130,] 1 20 [131,] 1 40 [132,] 0 60 [133,] 1 25 [134,] 1 45 [135,] 1 50 [136,] 0 25 [137,] 1 25 [138,] 1 50 [139,] 1 50 [140,] 1 0 [141,] 45 0 [142,] 35 1 [143,] 40 0 [144,] 30 1 [145,] 1 25 [146,] 1 55 [147,] 0 55 [148,] 1 45 [149,] 0 0 [150,] 55 0 [151,] 20 1 [152,] 45 1 [153,] 55 1 [154,] 45 0 [155,] 35 1 [156,] 35 1 [157,] 40 1 [158,] 0 35 [159,] 1 40 [160,] 1 50 [161,] 0 50 [162,] 1 50 [163,] 0 50 [164,] 0 35 [165,] 0 60 [166,] 0 45 [167,] 0 1 [168,] 45 1 [169,] 45 1 [170,] 0 40 [171,] 1 50 [172,] 1 30 [173,] 1 35 [174,] 1 0 [175,] 45 0 [176,] 55 1 [177,] 20 1 [178,] 55 1 [179,] 30 0 [180,] 25 1 [181,] 30 0 [182,] 60 1 [183,] 15 1 [184,] 30 0 [185,] 20 1 [186,] 1 20 [187,] 0 20 [188,] 1 25 [189,] 1 50 [190,] 0 55 [191,] 0 40 [192,] 1 30 [193,] 0 1 [194,] 65 0 [195,] 45 0 [196,] 35 1 [197,] 40 1 [198,] 30 1 [199,] 55 0 [200,] 50 0 [201,] 40 0 [202,] 35 1 [203,] 25 1 [204,] 60 0 [205,] 20 1 [206,] 65 0 [207,] 40 1 [208,] 1 25 [209,] 1 65 [210,] 0 30 [211,] 0 0 [212,] 50 0 [213,] 25 0 [214,] 30 0 [215,] 25 1 [216,] 20 0 [217,] 20 1 [218,] 30 1 [219,] 55 1 [220,] 50 0 [221,] 60 1 [222,] 40 0 [223,] 1 25 [224,] 0 0 [225,] 45 1 [226,] 35 0 [227,] 45 1 [228,] 0 35 [229,] 1 50 [230,] 0 40 [231,] 0 35 [232,] 1 55 [233,] 0 55 [234,] 1 35 [235,] 0 15 [236,] 1 20 [237,] 1 25 [238,] 1 65 [239,] 0 50 [240,] 1 1 [241,] 25 1 [242,] 1 35 [243,] 1 30 [244,] 1 35 [245,] 1 40 [246,] 1 35 [247,] 1 50 [248,] 0 40 [249,] 1 60 [250,] 1 30 [251,] 1 60 [252,] 0 60 [253,] 0 25 [254,] 0 0 [255,] 20 1 [256,] 25 1 [257,] 25 1 [258,] 10 1 [259,] 45 1 [260,] 40 1 [261,] 60 0 [262,] 1 35 [263,] 1 65 [264,] 0 55 [265,] 1 45 [266,] 1 55 [267,] 1 0 [268,] 65 1 [269,] 70 0 [270,] 65 0 [271,] 65 0 [272,] 50 1 [273,] 20 1 [274,] 55 0 [275,] 40 1 [276,] 50 1 [277,] 1 50 [278,] 0 20 [279,] 1 40 [280,] 1 1 [281,] 35 1 [282,] 40 0 [283,] 65 0 [284,] 50 0 [285,] 35 1 [286,] 65 0 [287,] 60 1 [288,] 60 0 [289,] 55 0 [290,] 25 0 [291,] 55 1 [292,] 35 1 [293,] 60 0 [294,] 45 1 [295,] 50 0 [296,] 30 0 [297,] 50 1 [298,] 25 1 [299,] 55 0 [300,] 25 1 [301,] 0 35 [302,] 1 1 [303,] 65 0 [304,] 40 1 [305,] 30 0 [306,] 30 1 [307,] 30 0 [308,] 20 0 [309,] 25 0 [310,] 35 0 [311,] 40 1 [312,] 60 0 [313,] 20 0 [314,] 25 0 [315,] 40 1 [316,] 30 0 [317,] 55 0 [318,] 35 1 [319,] 20 1 [320,] 30 0 [321,] 5 1 [322,] 5 1 [323,] 15 1 [324,] 40 1 [325,] 35 1 [326,] 20 1 [327,] 25 0 [328,] 30 0 [329,] 45 0 [330,] 30 0 [331,] 25 1 [332,] 15 1 [333,] 60 0 [334,] 40 1 [335,] 20 1 [336,] 25 0 [337,] 40 1 [338,] 25 0 [339,] 45 0 [340,] 45 1 [341,] 5 1 [342,] 30 1 [343,] 25 1 [344,] 35 1 [345,] 0 20 [346,] 0 45 [347,] 0 55 [348,] 0 55 [349,] 0 40 [350,] 0 30 [351,] 0 25 [352,] 1 45 [353,] 1 30 [354,] 0 30 [355,] 1 30 [356,] 0 30 [357,] 0 25 [358,] 1 10 [359,] 1 35 [360,] 0 35 [361,] 1 25 [362,] 1 30 [363,] 0 0 [364,] 25 0 [365,] 0 10 [366,] 1 20 [367,] 0 50 [368,] 1 30 [369,] 1 35 [370,] 0 20 [371,] 0 30 [372,] 0 25 [373,] 1 25 [374,] 0 20 [375,] 0 20 [376,] 1 35 [377,] 1 55 [378,] 0 10 [379,] 1 45 [380,] 0 35 [381,] 1 30 [382,] 1 30 [383,] 1 25 [384,] 0 25 [385,] 0 20 [386,] 0 40 [387,] 0 30 [388,] 1 20 [389,] 0 40 [390,] 0 0 [391,] 40 0 [392,] 35 0 [393,] 40 0 [394,] 35 0 [395,] 35 1 [396,] 20 0 [397,] 30 0 [398,] 50 0 [399,] 25 0 [400,] 25 0 [401,] 25 0 [402,] 25 0 [403,] 35 0 [404,] 30 0 [405,] 55 0 [406,] 30 0 [407,] 5 1 [408,] 25 1 [409,] 45 0 [410,] 10 1 [411,] 30 0 [412,] 65 1 [413,] 30 0 [414,] 10 1 [415,] 45 0 [416,] 45 1 [417,] 25 1 [418,] 25 1 [419,] 50 0 [420,] 50 1 [421,] 55 1 [422,] 25 0 [423,] 35 0 [424,] 25 0 [425,] 20 0 [426,] 20 1 [427,] 25 0 [428,] 40 0 [429,] 55 1 [430,] 50 0 [431,] 45 0 [432,] 30 1 [433,] 25 0 [434,] 45 1 [435,] 65 0 [436,] 60 0 [437,] 35 0 [438,] 20 1 [439,] 45 0 [440,] 25 1 [441,] 50 0 [442,] 25 0 [443,] 25 0 [444,] 35 0 [445,] 25 1 [446,] 35 0 [447,] 25 1 [448,] 25 0 [449,] 1 35 [450,] 0 45 [451,] 1 60 [452,] 0 0 [453,] 35 0 [454,] 30 0 [455,] 30 0 [456,] 0 5 [457,] 1 5 [458,] 1 25 [459,] 0 25 [460,] 1 20 [461,] 1 1 [462,] 35 1 [463,] 40 0 [464,] 25 0 [465,] 65 0 [466,] 50 0 [467,] 45 1 [468,] 60 0 [469,] 0 5 [470,] 1 35 [471,] 0 25 [472,] 1 0 [473,] 30 0 [474,] 40 0 [475,] 35 0 [476,] 30 0 [477,] 50 0 [478,] 15 1 [479,] 45 1 [480,] 20 1 [481,] 40 0 [482,] 50 0 [483,] 70 0 [484,] 30 0 [485,] 55 0 [486,] 40 0 [487,] 20 0 [488,] 65 0 [489,] 35 0 [490,] 15 1 [491,] 5 1 [492,] 5 1 [493,] 40 0 [494,] 30 0 [495,] 20 0 [496,] 30 0 [497,] 20 1 [498,] 30 1 [499,] 40 0 [500,] 25 1 [501,] 1 25 [502,] 0 30 [503,] 1 30 [504,] 0 0 [505,] 50 1 [506,] 20 0 [507,] 0 45 [508,] 0 25 [509,] 1 20 [510,] 1 45 [511,] 0 35 [512,] 1 35 [513,] 0 30 [514,] 1 30 [515,] 0 5 [516,] 1 10 [517,] 1 35 [518,] 1 40 [519,] 0 35 [520,] 0 30 [521,] 1 30 [522,] 1 25 [523,] 0 5 [524,] 1 5 [525,] 1 25 [526,] 1 50 [527,] 1 20 [528,] 0 25 [529,] 1 30 [530,] 0 25 [531,] 0 30 [532,] 0 25 [533,] 1 20 [534,] 1 20 [535,] 1 30 [536,] 1 60 [537,] 0 30 [538,] 1 35 [539,] 0 40 [540,] 1 25 [541,] 0 45 [542,] 0 25 [543,] 0 20 [544,] 0 15 [545,] 0 50 [546,] 1 25 [547,] 0 30 [548,] 1 30 [549,] 1 30 [550,] 0 30 [551,] 0 40 [552,] 0 35 [553,] 1 30 [554,] 0 25 [555,] 0 35 [556,] 1 0 [557,] 15 1 [558,] 40 1 [559,] 35 1 [560,] 30 0 [561,] 30 1 [562,] 5 1 [563,] 5 1 [564,] 30 1 [565,] 5 1 [566,] 5 1 [567,] 40 0 [568,] 35 1 [569,] 70 0 [570,] 0 35 [571,] 1 1 [572,] 30 1 [573,] 25 0 [574,] 45 0 [575,] 15 0 [576,] 20 0 [577,] 35 1 [578,] 20 1 [579,] 25 1 [580,] 20 1 [581,] 20 1 [582,] 30 0 [583,] 30 0 [584,] 40 0 [585,] 5 1 [586,] 20 1 [587,] 30 1 [588,] 30 0 [589,] 20 0 [590,] 25 0 [591,] 25 0 [592,] 35 0 [593,] 20 0 [594,] 35 0 [595,] 20 1 [596,] 5 0 [597,] 10 0 [598,] 5 0 [599,] 20 1 [600,] 40 0 [601,] 10 0 [602,] 15 0 [603,] 40 0 [604,] 30 1 [605,] 30 0 [606,] 40 0 [607,] 20 0 [608,] 30 0 [609,] 25 0 [610,] 20 0 [611,] 25 0 [612,] 35 0 [613,] 5 0 [614,] 10 0 [615,] 5 1 [616,] 15 0 [617,] 5 1 [618,] 40 0 [619,] 25 1 [620,] 40 1 [621,] 45 1 [622,] 25 0 [623,] 25 0 [624,] 20 0 [625,] 30 0 [626,] 25 0 [627,] 15 1 [628,] 20 0 [629,] 35 0 [630,] 35 1 [631,] 5 1 [632,] 5 1 [633,] 5 1 [634,] 25 1 [635,] 20 1 [636,] 40 0 [637,] 30 0 [638,] 20 1 [639,] 20 0 [640,] 45 0 [641,] 30 0 [642,] 25 0 [643,] 20 0 [644,] 30 0 [645,] 25 0 [646,] 0 20 [647,] 0 35 [648,] 1 25 [649,] 0 20 [650,] 0 30 [651,] 0 10 [652,] 0 10 [653,] 0 0 [654,] 0 0 [655,] 40 0 [656,] 35 0 [657,] 25 0 [658,] 25 1 [659,] 20 0 [660,] 30 0 [661,] 25 0 [662,] 25 0 [663,] 35 0 [664,] 20 0 [665,] 25 1 [666,] 20 0 [667,] 20 0 [668,] 25 0 [669,] 30 0 [670,] 20 0 [671,] 40 0 [672,] 20 0 [673,] 20 0 [674,] 25 0 [675,] 25 0 [676,] 25 0 [677,] 0 0 [678,] 30 0 [679,] 25 0 [680,] 20 1 [681,] 40 0 [682,] 30 0 [683,] 25 0 [684,] 25 0 [685,] 35 1 [686,] 30 0 [687,] 30 0 [688,] 20 0 [689,] 20 0 [690,] 20 1 [691,] 25 0 [692,] 40 0 [693,] 25 0 [694,] 35 0 [695,] 35 0 [696,] 25 1 [697,] 30 0 [698,] 75 0 [699,] 45 0 [700,] 35 0 [701,] 30 0 [702,] 20 0 [703,] 30 0 [704,] 10 1 [705,] 5 1 [706,] 40 1 [707,] 60 0 [708,] 20 0 [709,] 20 1 [710,] 45 0 [711,] 20 0 [712,] 25 0 [713,] 45 1 [714,] 25 0 [715,] 20 0 [716,] 30 1 [717,] 30 1 [718,] 5 0 [719,] 35 0 [720,] 30 0 [721,] 30 0 [722,] 25 0 [723,] 25 0 [724,] 25 0 [725,] 25 0 [726,] 20 0 [727,] 0 1 [728,] 40 1 [729,] 40 1 [730,] 30 1 [731,] 20 0 [732,] 5 1 [733,] 5 1 [734,] 30 0 [735,] 35 1 [736,] 25 0 [737,] 0 0 [738,] 25 0 [739,] 40 0 [740,] 20 1 [741,] 20 0 [742,] 45 0 [743,] 45 0 [744,] 0 35 [745,] 0 20 [746,] 1 30 [747,] 1 25 [748,] 0 25 [749,] 1 35 [750,] 0 65 [751,] 0 25 [752,] 1 25 [753,] 0 25 [754,] 1 20 [755,] 0 20 [756,] 0 45 [757,] 0 0 [758,] 40 0 [759,] 20 0 [760,] 15 0 [761,] 50 0 [762,] 5 1 [763,] 0 45 [764,] 0 45 [765,] 0 1 [766,] 20 0 [767,] 0 0 [768,] 0 30 [769,] 0 0 [770,] 1 25 [771,] 0 10 [772,] 0 0 [773,] 20 0 [774,] 20 0 [775,] 50 0 [776,] 0 0 [777,] 25 0 [778,] 0 0 [779,] 25 0 [780,] 20 1 [781,] 1 10 [782,] 1 35 [783,] 0 45 [784,] 0 35 [785,] 1 40 [786,] 0 10 [787,] 0 5 [788,] 0 15 [789,] 0 10 [790,] 0 20 [791,] 0 15 [792,] 0 40 [793,] 0 45 [794,] 0 55 [795,] 0 35 [796,] 0 0 [797,] 20 0 [798,] 40 0 [799,] 30 0 [800,] 20 0 [801,] 25 0 [802,] 20 0 [803,] 0 0 [804,] 30 0 [805,] 25 1 [806,] 20 0 [807,] 25 0 [808,] 45 0 [809,] 30 0 [810,] 25 0 [811,] 45 1 [812,] 0 25 [813,] 0 0 [814,] 15 0 [815,] 1 30 [816,] 1 1 [817,] 20 0 [818,] 30 1 [819,] 25 0 [820,] 25 1 [821,] 30 0 [822,] 30 0 [823,] 0 5 [824,] 1 25 [825,] 1 45 [826,] 0 30 [827,] 0 30 [828,] 1 0 [829,] 1 45 [830,] 0 1 [831,] 30 0 [832,] 0 30 [833,] 0 25 [834,] 0 0 [835,] 30 1 [836,] 25 1 [837,] 0 20 [838,] 0 50 [839,] 0 20 [840,] 0 1 [841,] 1 35 [842,] 0 30 [843,] 1 25 [844,] 0 35 [845,] 0 35 [846,] 0 30 [847,] 0 5 [848,] 1 5 [849,] 1 50 [850,] 0 35 [851,] 0 20 [852,] 0 30 [853,] 1 0 [854,] 0 0 [855,] 0 25 [856,] 0 35 [857,] 1 30 [858,] 0 20 [859,] 0 25 [860,] 0 35 [861,] 1 20 [862,] 0 25 [863,] 0 30 [864,] 0 25 [865,] 1 35 [866,] 0 25 [867,] 0 5 [868,] 1 40 [869,] 1 0 [870,] 20 0 [871,] 0 0 [872,] 1 1 [873,] 35 0 [874,] 45 0 [875,] 1 0 [876,] 0 0 [877,] 0 0 [878,] 25 0 [879,] 30 0 [880,] 5 1 [881,] 30 1 [882,] 30 1 [883,] 5 0 [884,] 20 0 [885,] 40 0 [886,] 0 25 [887,] 1 0 [888,] 40 0 [889,] 0 1 [890,] 0 25 [891,] 1 0 [892,] 30 1 [893,] 30 0 [894,] 30 0 [895,] 25 0 [896,] 25 1 [897,] 0 0 [898,] 0 0 [899,] 0 35 [900,] 0 35 [901,] 0 0 [902,] 0 40 [903,] 0 40 [904,] 0 25 [905,] 0 25 [906,] 0 45 [907,] 0 40 [908,] 0 30 [909,] 0 20 [910,] 1 0 [911,] 30 0 [912,] 0 30 [913,] 0 30 [914,] 0 0 [915,] 25 0 [916,] 30 1 [917,] 55 0 [918,] 25 1 [919,] 35 1 [920,] 0 0 [921,] 1 25 [922,] 1 25 [923,] 0 0 [924,] 0 0 [925,] 30 0 [926,] 1 35 [927,] 0 1 [928,] 0 35 [929,] 0 35 [930,] 0 1 [931,] 0 1 [932,] 1 1 [933,] 1 1 [934,] 1 0 [935,] 1 15 [936,] 1 35 [937,] 0 0 [938,] 25 0 [939,] 20 0 [940,] 0 0 [941,] 0 60 [942,] 0 0 [943,] 25 1 [944,] 0 25 [945,] 0 25 [946,] 0 30 [947,] 0 0 [948,] 1 25 [949,] 0 10 [950,] 1 30 [951,] 1 0 [952,] 1 0 [953,] 0 35 [954,] 0 0 [955,] 1 1 [956,] 1 1 [957,] 1 0 [958,] 1 25 [959,] 1 0 [960,] 1 1 [961,] 1 20 [962,] 0 25 [963,] 0 15 [964,] 1 5 [965,] 1 20 [966,] 1 20 [967,] 1 35 [968,] 0 0 [969,] 0 0 [970,] 0 15 [971,] 1 15 [972,] 1 30 [973,] 0 30 [974,] 0 20 [975,] 1 30 [976,] 1 25 [977,] 0 45 [978,] 0 40 [979,] 1 25 [980,] 0 30 [981,] 0 25 [982,] 1 65 [983,] 0 0 [984,] 0 1 [985,] 0 0 [986,] 0 25 [987,] 0 0 [988,] 1 1 [989,] 25 1 [990,] 1 1 [991,] 10 1 [992,] 30 0 [993,] 45 0 [994,] 0 35 [995,] 0 30 [996,] 0 35 [997,] 1 20 [998,] 0 25 [999,] 0 20 [1000,] 0 20 [1001,] 0 20 [1002,] 0 35 [1003,] 1 0 [1004,] 0 5 [1005,] 0 10 [1006,] 0 5 [1007,] 0 10 [1008,] 0 30 [1009,] 0 5 [1010,] 0 10 [1011,] 0 5 [1012,] 0 20 [1013,] 0 15 [1014,] 0 45 [1015,] 0 25 [1016,] 0 20 [1017,] 0 0 [1018,] 35 0 [1019,] 5 0 [1020,] 5 0 [1021,] 30 0 [1022,] 0 0 [1023,] 0 25 [1024,] 0 25 [1025,] 0 25 [1026,] 0 25 [1027,] 1 1 [1028,] 1 1 [1029,] 0 25 [1030,] 0 30 [1031,] 0 20 [1032,] 0 0 [1033,] 0 25 [1034,] 0 20 [1035,] 0 35 [1036,] 1 0 [1037,] 20 0 [1038,] 25 0 [1039,] 0 0 [1040,] 0 0 [1041,] 40 0 [1042,] 25 0 [1043,] 10 0 [1044,] 5 0 [1045,] 10 0 [1046,] 5 0 [1047,] 10 0 [1048,] 40 0 [1049,] 25 0 [1050,] 35 0 [1051,] 1 0 [1052,] 0 50 [1053,] 0 50 [1054,] 0 0 [1055,] 0 5 [1056,] 0 20 [1057,] 0 45 [1058,] 0 1 [1059,] 50 0 [1060,] 20 0 [1061,] 1 0 [1062,] 0 25 [1063,] 0 0 [1064,] 0 0 [1065,] 40 0 [1066,] 0 15 [1067,] 0 0 [1068,] 0 0 [1069,] 0 0 [1070,] 0 0 [1071,] 0 0 [1072,] 25 0 [1073,] 25 1 [1074,] 40 0 [1075,] 0 0 [1076,] 0 5 [1077,] 1 25 [1078,] 1 5 [1079,] 1 25 [1080,] 1 20 [1081,] 0 25 [1082,] 0 0 [1083,] 0 0 [1084,] 30 1 [1085,] 0 1 [1086,] 0 0 [1087,] 25 0 [1088,] 0 40 [1089,] 0 25 [1090,] 0 20 [1091,] 1 5 [1092,] 0 10 [1093,] 0 10 [1094,] 0 5 [1095,] 0 40 [1096,] 0 45 [1097,] 0 0 [1098,] 0 0 [1099,] 0 1 [1100,] 20 0 [1101,] 30 0 [1102,] 0 35 [1103,] 0 0 [1104,] 35 0 [1105,] 25 1 [1106,] 25 0 [1107,] 65 0 [1108,] 20 0 [1109,] 25 0 [1110,] 35 1 [1111,] 30 0 [1112,] 5 0 [1113,] 30 0 [1114,] 20 1 [1115,] 45 1 [1116,] 25 0 [1117,] 75 0 [1118,] 15 1 [1119,] 25 0 [1120,] 25 1 [1121,] 35 0 [1122,] 5 1 [1123,] 0 0 [1124,] 0 20 [1125,] 1 0 [1126,] 0 1 [1127,] 35 0 [1128,] 0 0 [1129,] 35 0 [1130,] 45 0 [1131,] 0 0 [1132,] 25 1 [1133,] 0 10 [1134,] 1 10 [1135,] 1 30 [1136,] 1 40 [1137,] 0 20 [1138,] 1 65 [1139,] 1 0 [1140,] 15 0 [1141,] 45 0 [1142,] 10 0 [1143,] 40 0 [1144,] 30 0 [1145,] 0 35 [1146,] 0 30 [1147,] 0 30 [1148,] 0 50 [1149,] 0 20 [1150,] 0 35 [1151,] 0 20 [1152,] 0 35 [1153,] 0 25 [1154,] 1 20 [1155,] 0 15 [1156,] 0 25 [1157,] 0 25 [1158,] 0 0 [1159,] 0 0 [1160,] 35 0 [1161,] 40 1 [1162,] 55 0 [1163,] 20 0 [1164,] 25 0 [1165,] 50 1 [1166,] 0 0 [1167,] 0 30 [1168,] 0 25 [1169,] 0 30 [1170,] 0 0 [1171,] 0 40 [1172,] 0 30 [1173,] 0 15 [1174,] 1 50 [1175,] 0 0 [1176,] 0 15 [1177,] 0 0 [1178,] 30 0 [1179,] 30 0 [1180,] 0 30 [1181,] 1 5 [1182,] 1 5 [1183,] 0 30 [1184,] 0 25 [1185,] 0 50 [1186,] 1 65 [1187,] 1 40 [1188,] 0 55 [1189,] 1 75 [1190,] 0 50 [1191,] 0 20 [1192,] 1 25 [1193,] 1 30 [1194,] 1 80 [1195,] 1 0 [1196,] 25 0 [1197,] 50 1 [1198,] 35 1 [1199,] 40 0 [1200,] 40 1 [1201,] 50 1 [1202,] 30 1 [1203,] 45 1 [1204,] 30 1 [1205,] 25 0 [1206,] 25 1 [1207,] 20 1 [1208,] 35 1 [1209,] 30 1 [1210,] 45 0 [1211,] 40 1 [1212,] 30 1 [1213,] 60 1 [1214,] 45 0 [1215,] 45 1 [1216,] 25 1 [1217,] 1 45 [1218,] 0 50 [1219,] 0 0 [1220,] 45 1 [1221,] 60 1 [1222,] 60 1 [1223,] 45 1 [1224,] 45 0 [1225,] 0 45 [1226,] 1 55 [1227,] 1 40 [1228,] 1 60 [1229,] 1 35 [1230,] 0 30 [1231,] 0 20 [1232,] 0 15 [1233,] 1 15 [1234,] 1 40 [1235,] 1 40 [1236,] 1 50 [1237,] 0 1 [1238,] 40 0 [1239,] 80 1 [1240,] 50 0 [1241,] 50 1 [1242,] 30 1 [1243,] 35 1 [1244,] 40 1 [1245,] 30 1 [1246,] 45 1 [1247,] 1 0 [1248,] 30 0 [1249,] 30 1 [1250,] 25 1 [1251,] 0 50 [1252,] 0 40 [1253,] 1 40 [1254,] 0 65 [1255,] 1 55 [1256,] 1 0 [1257,] 70 0 [1258,] 40 1 [1259,] 65 1 [1260,] 40 0 [1261,] 40 1 [1262,] 55 1 [1263,] 30 1 [1264,] 35 1 [1265,] 35 0 [1266,] 30 1 [1267,] 35 1 [1268,] 20 1 [1269,] 55 1 [1270,] 5 1 [1271,] 55 1 [1272,] 50 0 [1273,] 30 1 [1274,] 50 1 [1275,] 50 1 [1276,] 50 1 [1277,] 40 0 [1278,] 25 1 [1279,] 40 1 [1280,] 55 1 [1281,] 40 0 [1282,] 0 1 [1283,] 1 40 [1284,] 1 30 [1285,] 0 25 [1286,] 1 30 [1287,] 1 25 [1288,] 1 20 [1289,] 0 65 [1290,] 0 60 [1291,] 1 30 [1292,] 1 0 [1293,] 0 50 [1294,] 1 45 [1295,] 1 1 [1296,] 25 1 [1297,] 60 1 [1298,] 50 1 [1299,] 0 40 [1300,] 0 35 [1301,] 1 50 [1302,] 0 35 [1303,] 1 25 [1304,] 1 45 [1305,] 1 25 [1306,] 0 50 [1307,] 1 1 [1308,] 75 0 [1309,] 55 1 > (table1 <- table(z[,cat1],z[,cat2])) 0 1 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 0 76 17 15 14 12 34 53 43 36 23 18 17 9 5 3 1 0 1 1 29 21 9 4 3 21 38 36 28 21 17 22 10 9 7 0 2 1 5 11 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 7 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 6 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 20 52 31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 74 43 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 30 68 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 32 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 40 42 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 45 25 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 50 22 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 55 10 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 60 9 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 65 12 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 70 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 80 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 > (V1<-dimnames(y)[[1]][cat1]) [1] "age" > (V2<-dimnames(y)[[1]][cat2]) [1] "survived\r" > postscript(file="/var/www/html/rcomp/tmp/10era1291995566.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > assoc(ftable(z[,cat1],z[,cat2],row.vars=1,dnn=c(V1,V2)),shade=T) Warning message: In grid.Call.graphics("L_text", as.graphicsAnnot(x$label), x$x, : font width unknown for character 0xd > dev.off() null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Tabulation of Results',ncol(table1)+1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, ' ', 1,TRUE) > for(nc in 1:ncol(table1)){ + a<-table.element(a, colnames(table1)[nc], 1, TRUE) + } > a<-table.row.end(a) > for(nr in 1:nrow(table1) ){ + a<-table.element(a, rownames(table1)[nr], 1, TRUE) + for(nc in 1:ncol(table1) ){ + a<-table.element(a, table1[nr, nc], 1, FALSE) + } + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/2lf8y1291995566.tab") > (cst<-chisq.test(table1, simulate.p.value=simulate.p.value) ) Pearson's Chi-squared test data: table1 X-squared = 948.5045, df = 289, p-value < 2.2e-16 Warning message: In chisq.test(table1, simulate.p.value = simulate.p.value) : Chi-squared approximation may be incorrect > if (par3 == 'McNemar Chi-Squared') { + (cst <- mcnemar.test(table1)) + } > if (par3 != 'McNemar Chi-Squared') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Tabulation of Expected Results',ncol(table1)+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a, ' ', 1,TRUE) + for(nc in 1:ncol(table1)){ + a<-table.element(a, colnames(table1)[nc], 1, TRUE) + } + a<-table.row.end(a) + for(nr in 1:nrow(table1) ){ + a<-table.element(a, rownames(table1)[nr], 1, TRUE) + for(nc in 1:ncol(table1) ){ + a<-table.element(a, round(cst$expected[nr, nc], digits=2), 1, FALSE) + } + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/36xom1291995566.tab") + } > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Statistical Results',2,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, cst$method, 2,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Chi Square Statistic', 1, TRUE) > a<-table.element(a, round(cst$statistic, digits=2), 1,FALSE) > a<-table.row.end(a) > if(!simulate.p.value){ + a<-table.row.start(a) + a<-table.element(a, 'Degrees of Freedom', 1, TRUE) + a<-table.element(a, cst$parameter, 1,FALSE) + a<-table.row.end(a) + } > a<-table.row.start(a) > a<-table.element(a, 'P value', 1, TRUE) > a<-table.element(a, round(cst$p.value, digits=2), 1,FALSE) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/4ag5a1291995566.tab") > > try(system("convert tmp/10era1291995566.ps tmp/10era1291995566.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.038 0.267 8.108