-
Notifications
You must be signed in to change notification settings - Fork 0
/
data.R
254 lines (245 loc) · 16.4 KB
/
data.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
###############################################################################
#
# Data for R-replication of reliability analyses
# - DECA (deca, decaB, decaM, decaR, decaW) is a sample dataset distributed
# within Survo software (https://www.survo.fi), see Chapter 5.1 in
# Vehkalahti 2000. http://hdl.handle.net/10138/10570
# - Correlation matrix (CRF) from the example of Religiosity and Fatalism in
# Heise & Bohrnstedt (1970). Validity, invalidity and reliability. In
# Borgatta, E. F. and Bohrnstedt, G. W. (eds.), Sociological Methodology.
# Jossey-Bass, San Francisco. pp. 104−129.
# - Factor and moment matrices related with CRF (FRF, MRF) calculated as
# in pages 50-51 of Vehkalahti 2000. http://hdl.handle.net/10138/10570
#
# Author(s):
# Reijo Sund (ORCID: 0000-0002-6268-8117), https://connect.uef.fi/en/reijo.sund
#
###############################################################################
deca <- structure(list(
Name = c("Skowrone", "Hedmark ", "Le_Roy ", "Zeilbaue", "Zigert ", "Bennett ",
"Blinjaje", "Katus ", "Berendse", "Gorbacho", "Kiseljev", "Gough ",
"Sherbati", "Ghesquir", "Avilov ", "Kratky ", "Schreyer", "Linkmann",
"Thiemig ", "Pernica ", "Stroot ", "Bugay ", "Evans ", "Tselnoko",
"Ivanov ", "Janczenk", "Demmig ", "Schulze ", "Andres ", "George ",
"Jenner ", "Swoboda ", "Apt ", "Herbrand", "Tregubje", "Kozakiew",
"Jachmien", "Pold ", "Nikitin ", "Ormanov ", "Brigham ", "Hoischen",
"Wanamake", "Novik ", "Samara ", "Schoebel", "Bogdan ", "Dzhurov "),
Points = c(8206L, 8188L, 8140L, 8136L, 8134L, 8121L, 8100L, 8020L, 8016L, 7977L, 7949L, 7938L,
7927L, 7905L, 7903L, 7876L, 7865L, 7849L, 7848L, 7844L, 7842L, 7840L, 7819L, 7812L,
7812L, 7806L, 7804L, 7799L, 7794L, 7777L, 7771L, 7769L, 7750L, 7743L, 7733L, 7679L,
7692L, 7686L, 7680L, 7676L, 7673L, 7663L, 7662L, 7662L, 7651L, 7650L, 7651L, 7649L),
X100m = c(853L, 853L, 879L, 826L, 879L, 905L, 879L, 853L, 804L, 853L, 879L, 756L,
853L, 756L, 712L, 828L, 853L, 905L, 905L, 804L, 932L, 780L, 756L, 853L,
780L, 864L, 905L, 905L, 828L, 780L, 804L, 853L, 828L, 804L, 756L, 780L,
756L, 828L, 905L, 905L, 733L, 733L, 756L, 828L, 932L, 828L, 759L, 747L),
L_jump = c(931L, 853L, 951L, 931L, 840L, 859L, 848L, 828L, 848L, 830L, 869L, 945L,
887L, 820L, 863L, 909L, 875L, 861L, 774L, 802L, 881L, 794L, 780L, 832L,
791L, 889L, 828L, 816L, 828L, 867L, 816L, 842L, 808L, 877L, 861L, 804L,
806L, 728L, 828L, 725L, 767L, 782L, 857L, 814L, 909L, 806L, 871L, 798L),
Shot_put = c(725L, 814L, 799L, 793L, 924L, 647L, 785L, 772L, 795L, 815L, 792L, 798L,
643L, 773L, 734L, 730L, 782L, 763L, 751L, 675L, 644L, 702L, 772L, 759L,
711L, 760L, 765L, 769L, 612L, 654L, 726L, 701L, 768L, 743L, 736L, 665L,
774L, 760L, 751L, 751L, 777L, 712L, 685L, 742L, 604L, 647L, 722L, 835L),
Hi_jump = c(857L, 769L, 779L, 865L, 857L, 779L, 804L, 751L, 831L, 822L, 891L, 831L,
840L, 813L, 925L, 796L, 804L, 788L, 804L, 822L, 769L, 900L, 925L, 725L,
891L, 891L, 707L, 707L, 788L, 769L, 857L, 769L, 743L, 857L, 769L, 788L,
900L, 813L, 751L, 725L, 917L, 857L, 813L, 822L, 707L, 715L, 689L, 689L),
X400m = c(838L, 833L, 838L, 875L, 788L, 938L, 766L, 838L, 819L, 784L, 784L, 762L,
838L, 847L, 788L, 838L, 766L, 792L, 889L, 819L, 898L, 852L, 792L, 842L,
784L, 819L, 889L, 829L, 880L, 866L, 797L, 797L, 801L, 732L, 736L, 829L,
762L, 788L, 880L, 838L, 699L, 716L, 842L, 740L, 779L, 819L, 810L, 792L),
Hurdles = c(903L, 914L, 881L, 891L, 892L, 859L, 807L, 987L, 837L, 817L, 938L, 892L,
892L, 827L, 883L, 903L, 881L, 962L, 870L, 870L, 859L, 870L, 777L, 777L,
881L, 726L, 938L, 881L, 837L, 851L, 848L, 797L, 837L, 903L, 827L, 757L,
777L, 848L, 817L, 837L, 748L, 848L, 848L, 870L, 837L, 848L, 799L, 789L),
Discus = c(772L, 855L, 819L, 729L, 866L, 651L, 897L, 748L, 801L, 762L, 731L, 874L,
607L, 808L, 758L, 722L, 795L, 794L, 787L, 695L, 710L, 725L, 784L, 746L,
715L, 773L, 738L, 752L, 671L, 626L, 774L, 709L, 749L, 719L, 732L, 653L,
799L, 774L, 657L, 765L, 809L, 688L, 744L, 741L, 717L, 722L, 658L, 757L),
Pole_vlt = c(981L, 884L, 1028L, 909L, 920L, 1028L, 909L, 960L, 884L, 859L, 807L, 807L,
932L, 807L, 909L, 859L, 884L, 909L, 884L, 957L, 832L, 859L, 874L, 832L,
909L, 909L, 832L, 909L, 957L, 932L, 837L, 859L, 981L, 884L, 981L, 1052L,
832L, 859L, 809L, 920L, 1005L, 859L, 780L, 909L, 957L, 909L, 909L, 909L),
Javelin = c(818L, 975L, 758L, 774L, 671L, 794L, 820L, 755L, 755L, 848L, 762L, 794L,
781L, 807L, 772L, 695L, 767L, 665L, 679L, 721L, 731L, 703L, 828L, 889L,
842L, 797L, 701L, 731L, 736L, 736L, 765L, 834L, 675L, 703L, 748L, 740L,
745L, 696L, 677L, 650L, 738L, 856L, 773L, 761L, 704L, 820L, 765L, 726L),
X1500m = c(528L, 438L, 408L, 543L, 497L, 661L, 585L, 528L, 642L, 587L, 496L, 479L,
654L, 647L, 559L, 596L, 458L, 410L, 505L, 679L, 586L, 655L, 531L, 557L,
508L, 378L, 499L, 500L, 657L, 696L, 547L, 608L, 560L, 521L, 587L, 629L,
541L, 592L, 605L, 560L, 480L, 612L, 564L, 435L, 505L, 536L, 669L, 604L),
Height = c(184L, 195L, 191L, 192L, 198L, 173L, 190L, 184L, 189L, 186L, 191L, 190L,
183L, 190L, 190L, 185L, 184L, 195L, 194L, 188L, 182L, 190L, 188L, 191L,
186L, 182L, 188L, 184L, 180L, 184L, 188L, 182L, 190L, 190L, 184L, 177L,
192L, 190L, 182L, 187L, 184L, 187L, 188L, 175L, 183L, 188L, 186L, 194L),
Weight = c(81L, 90L, 90L, 84L, 105L, 68L, 90L, 81L, 89L, 87L, 91L, 93L,
82L, 87L, 87L, 85L, 84L, 100L, 94L, 83L, 78L, 83L, 95L, 94L,
86L, 81L, 86L, 82L, 68L, 82L, 84L, 75L, 89L, 88L, 86L, 76L,
90L, 86L, 85L, 84L, 87L, 83L, 88L, 78L, 80L, 88L, 81L, 93L)
),
class = "data.frame",
row.names = c(NA, 48L),
status.info = "Survo data file DECA: record=62 bytes, M1=21 L=64 M=14 N=48",
status.description = "Best athletes in decathlon in 1973",
status.varname = c("Name Name of athlete ",
"Points Total score (####) {7000,9000}",
"100m 100 meters run (####) {500,1200} ",
"L_jump Long jump (####) {500,1200} ",
"Shot_put (####) {500,1200} ",
"Hi_jump High jump (####) {500,1200} ",
"400m 400 meters run (####) {500,1200} ",
"Hurdles 110 meters hurdles (####) {500,1200} ",
"Discus (####) {500,1200} ",
"Pole_vlt Pole vault (####) {500,1200} ",
"Javelin (####) {500,1200} ",
"1500m 1500 meters run (####) {400,1200} ",
"Height in centimeters (###) {160,210} ",
"Weight in kilograms (###) {50,120} ")
)
decaB <- structure(
c(0.874767959117889, 0.0615563690662384, -0.148137018084526, -0.501938819885254, 0.591720223426819,
0.127185106277466, -0.140840485692024, 0.0319532491266727, -0.149811819195747, 0.0520788319408894,
-0.0379974097013474, -0.0399567782878876, 0.746573805809021, 0.105960980057716, -0.0962432995438576,
0.121835112571716, 0.660480976104736, -0.319848895072937, 0.109378099441528, -0.136724308133125,
-0.321904063224792, -0.101388417184353, -0.39337494969368, -0.106276825070381, 0.3485426902771,
-0.0456685833632946, -0.548516273498535, -0.0585124641656876, -0.0167780853807926, 0.88499641418457,
-0.11963377892971, 0.199750974774361, -0.109704621136189, 0.0857827663421631, 0.00600633583962917,
-0.192777097225189, 0.0443446710705757, -0.0972429662942886, 0.791407823562622, -0.0312026515603065,
0.240357369184494, 0.4614237844944, -0.0361479073762894, 0.03164092451334, 0.199148148298264,
0.709934055805206, -0.0384790115058422, -0.0566012039780617, 0.0126882856711745, -0.254859268665314),
.Dim = c(10L, 5L),
.Dimnames = list(c("X100m", "L_jump", "Shot_put", "Hi_jump", "X400m",
"Hurdles", "Discus", "Pole_vlt", "Javelin", "X1500m"),
c("F1", "F2", "F3", "F4", "F5"))
)
decaM <- structure(
c(828.1875, 840.1875, 740.770812988281, 805.854187011719,
813.5, 852.875, 747.458312988281, 900.270812988281, 760.020812988281,
554.625, 59.302562713623, 50.728588104248, 61.8275718688965,
64.8051071166992, 49.8021621704102, 54.2047424316406, 62.2821159362793,
63.0429573059082, 63.9369659423828, 76.6724548339844),
.Dim = c(10L, 2L),
.Dimnames = list(c("X100m", "L_jump", "Shot_put", "Hi_jump", "X400m",
"Hurdles", "Discus", "Pole_vlt", "Javelin", "X1500m"),
c("mean", "stddev"))
)
decaR <- structure(
c(1, 0.171985357999802, -0.0279522985219955, -0.411699533462524,
0.456081569194794, 0.315991163253784, 0.0143430950120091, 0.054722610861063,
-0.221250101923943, -0.291744232177734, 0.171985357999802, 1,
-0.0343929789960384, -0.00332459807395935, 0.133463323116302,
0.298065036535263, 0.0208751782774925, 0.0610243938863277, 0.153749749064445,
-0.206665351986885, -0.0279522985219955, -0.0343929789960384,
1, 0.162541955709457, -0.303707391023636, 0.0864982306957245,
0.727329850196838, -0.204229161143303, 0.0231397431343794, -0.446248471736908,
-0.411699533462524, -0.00332459807395935, 0.162541955709457,
1, -0.338827192783356, -0.0389637500047684, 0.216994792222977,
-0.117765076458454, 0.149778574705124, -0.146149665117264, 0.456081569194794,
0.133463323116302, -0.303707391023636, -0.338827192783356, 1,
0.175547793507576, -0.344647228717804, 0.00658355047926307, -0.104689136147499,
0.302177548408508, 0.315991163253784, 0.298065036535263, 0.0864982306957245,
-0.0389637500047684, 0.175547793507576, 1, 0.0477070994675159,
-0.0734972804784775, -0.148187592625618, -0.224551722407341,
0.0143430950120091, 0.0208751782774925, 0.727329850196838, 0.216994792222977,
-0.344647228717804, 0.0477070994675159, 1, -0.181800127029419,
0.135560631752014, -0.573501408100128, 0.054722610861063, 0.0610243938863277,
-0.204229161143303, -0.117765076458454, 0.00658355047926307,
-0.0734972804784775, -0.181800127029419, 1, -0.128523245453835,
0.0124960420653224, -0.221250101923943, 0.153749749064445, 0.0231397431343794,
0.149778574705124, -0.104689136147499, -0.148187592625618, 0.135560631752014,
-0.128523245453835, 1, -0.0654140189290047, -0.291744232177734,
-0.206665351986885, -0.446248471736908, -0.146149665117264, 0.302177548408508,
-0.224551722407341, -0.573501408100128, 0.0124960420653224, -0.0654140189290047,
1),
.Dim = c(10L, 10L),
.Dimnames = list(c("X100m", "L_jump", "Shot_put", "Hi_jump", "X400m",
"Hurdles", "Discus", "Pole_vlt", "Javelin", "X1500m"),
c("X100m", "L_jump", "Shot_put", "Hi_jump", "X400m",
"Hurdles", "Discus", "Pole_vlt", "Javelin", "X1500m")
)
)
decaW <- structure(
c(0.0159732457250357, -0.000641106104012579, 0.000482244446175173,
-0.00100321997888386, 0.00203931704163551, -0.00202594208531082,
0.000556881190277636, -0.000241128291236237, 0.00126457319129258,
0.00385456415824592, 0.000541315181180835, -0.000113951711682603,
0.00948676932603121, -9.95507798506878e-05, 0.00183932238724083,
0.0022008151281625, 0.00741217331960797, -0.00165888469200581,
0.00128811888862401, 0.00525358784943819, -0.00367015297524631,
0.000602823856752366, 0.000683267135173082, -0.000305006513372064,
0.00314712198451161, 0.00300287152640522, -0.00145413796417415,
-0.000851832737680525, 0.000461595365777612, 0.0102205378934741,
0.000506917538587004, 0.00187600392382592, -0.00248996377922595,
9.64198188739829e-05, 0.00134528882335871, -0.00241774204187095,
0.000758669106289744, -0.000614472664892673, 0.0118782380595803,
-0.000560335000045598, -0.00122312468010932, 0.00438994634896517,
-0.00106193905230612, 0.00096036319155246, 0.00244591454975307,
0.0113399578258395, -0.00224330555647612, -0.00068486190866679,
0.000893420190550387, -0.00293241045437753),
.Dim = c(10L, 5L),
.Dimnames = list(
c("X100m", "L_jump", "Shot_put", "Hi_jump", "X400m",
"Hurdles", "Discus", "Pole_vlt", "Javelin", "X1500m"),
c("Speed", "Force", "Streng", "Tech1", "Tech2"))
)
CRF <- structure(
c(1, 0.533034861087799, 0.509937047958374, 0.420490354299545,
0.542386054992676, 0.498733252286911, 0.148389205336571, 0.0293094720691442,
0.0587776042521, -0.0352831520140171, 0.0599234737455845, 0.533034861087799,
1, 0.496695756912231, 0.378507703542709, 0.49680957198143, 0.458608865737915,
0.16809768974781, -0.0216288901865482, 0.0265199579298496, 0.00813661329448223,
0.0225308034569025, 0.509937047958374, 0.496695756912231, 1,
0.419904887676239, 0.490160375833511, 0.489342004060745, 0.195480152964592,
0.00379996560513973, 0.00414157705381513, 0.00457445159554482,
0.00562975602224469, 0.420490354299545, 0.378507703542709, 0.419904887676239,
1, 0.51128751039505, 0.55056095123291, 0.0132618062198162, 0.00597232207655907,
0, 0, 0.00530889770016074, 0.542386054992676, 0.49680957198143,
0.490160375833511, 0.51128751039505, 1, 0.686923563480377, 0.0137769374996424,
-0.0027574694249779, 0.0360643416643143, -0.0315350629389286,
0.00612790277227759, 0.498733252286911, 0.458608865737915, 0.489342004060745,
0.55056095123291, 0.686923563480377, 1, 0.137089669704437, 0.0215229783207178,
-0.0148154925554991, 0.0259096641093493, 0.0616759769618511,
0.148389205336571, 0.16809768974781, 0.195480152964592, 0.0132618062198162,
0.0137769374996424, 0.137089669704437, 1, 0.239331632852554,
0.226890757679939, 0.187527731060982, 0.267505973577499, 0.0293094720691442,
-0.0216288901865482, 0.00379996560513973, 0.00597232207655907,
-0.0027574694249779, 0.0215229783207178, 0.239331632852554, 1,
0.310009390115738, 0.155083179473877, 0.170073390007019, 0.0587776042521,
0.0265199579298496, 0.00414157705381513, 0, 0.0360643416643143,
-0.0148154925554991, 0.226890757679939, 0.310009390115738, 1,
0.197474673390388, 0.206988379359245, -0.0352831520140171, 0.00813661329448223,
0.00457445159554482, 0, -0.0315350629389286, 0.0259096641093493,
0.187527731060982, 0.155083179473877, 0.197474673390388, 1, 0.418004155158997,
0.0599234737455845, 0.0225308034569025, 0.00562975602224469,
0.00530889770016074, 0.00612790277227759, 0.0616759769618511,
0.267505973577499, 0.170073390007019, 0.206988379359245, 0.418004155158997, 1),
.Dim = c(11L, 11L),
.Dimnames = list(c("Item1", "Item2", "Item3", "Item4", "Item5", "Item6",
"Item7", "Item8", "Item9", "Item10", "Item11"),
c("Item1", "Item2", "Item3", "Item4", "Item5", "Item6",
"Item7", "Item8", "Item9", "Item10", "Item11"))
)
FRF <- structure(
c(0.693569362163544, 0.646963477134705, 0.659234821796417, 0.639006674289703,
0.804113030433655, 0.792293608188629, 0.155455201864243, 0.0221087466925383,
0.0368843525648117, 0.00573471654206514, 0.0545658692717552, 0.029903469607234,
0.0203159116208553, 0.0174197051674128, -0.0604462884366512, -0.0841521248221397,
-0.000940427358727902, 0.465761363506317, 0.3897565305233, 0.425217270851135,
0.538043797016144, 0.597876667976379),
.Dim = c(11L, 2L),
.Dimnames = list(c("Item1", "Item2", "Item3", "Item4", "Item5", "Item6",
"Item7", "Item8", "Item9", "Item10", "Item11"),
c("F1", "F2"))
)
MRF <- structure(
c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0.963327586650848, 0.83546394109726, 0.891627728939056, 0.945515751838684,
0.819145917892456, 0.996995508670807, 0.79749608039856, 0.885437726974487,
0.812403857707977, 0.735527038574219, 0.796868860721588,
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500),
.Dim = c(11L, 3L),
.Dimnames = list(
c("Item1", "Item2", "Item3", "Item4", "Item5", "Item6",
"Item7", "Item8", "Item9", "Item10", "Item11"),
c("mean", "stddev", "N"))
)