This is not a bug. You forgot to use the header=TRUE argument to read.table(),
so your variables weren't recognized as numeric.
Please don't use r-bugs unless you are sure there is a bug in R. Use r-help to
ask for help.
-thomas
On Wed, 18 Mar 2009 michael_ka...@earthlink.net wrote:
Full_Name: Michael Aaron Karsh
Version: 2.8.0
OS: Windows XP
Submission from: (NULL) (75.61.109.172)
I tried using the lm function to regress the third column listed below on the
second column listed below. It gave me an error message. My code is below.
HDISWLSdata=read.table("RHDISWLS.txt")
HDISWLSdata
V1 V2 V3
1 DENMARK .82 .949
2 SWITZERLAND .82 .955
3 AUSTRIA .78 .948
4 ICELAND .78 .968
5 BAHAMAS .77 .845
6 FINLAND .77 .952
7 SWEDEN .77 .956
8 BHUTAN .76 .579
9 BRUNEIDARUSSALAM .76 .894
10 CANADA .76 .961
11 IRELAND .76 .959
12 LUXEMBOURG .76 .944
13 COSTARICA .75 .846
14 MALTA .75 .878
15 NETHERLANDS .75 .953
16 ANTIGUAANDBARBUDA .74 .815
17 MALAYSIA .74 .811
18 NEWZEALAND .74 .943
19 NORWAY .74 .968
20 SEYCHELLES .74 .843
21 STKITTSANDNEVIS .74 .821
22 UAE .74 .868
23 USA .74 .951
24 VANUATU .74 .674
25 VENEZUELA .74 .792
26 AUSTRALIA .73 .962
27 BARBADOS .73 .892
28 BELGIUM .73 .946
29 DOMINICA .73 .798
30 OMAN .73 .814
31 SAUDIARABIA .73 .812
32 SURINAME .73 .774
33 BAHRAIN .72 .866
34 COLUMBIA .72 .791
35 GERMANY .72 .935
36 GUYANA .72 .75
37 HONDURAS .72 .7
38 KUWAIT .72 .891
39 PANAMA .72 .812
40 STVINCENTANDTHEGRENADINES .72 .761
41 UNITEDKINGDOM .71 .946
42 DOMINICANREPUBLIC .7 .779
43 GUATEMALA .7 .689
44 JAMAICA .7 .736
45 QATAR .7 .875
46 SPAIN .7 .949
47 STLUCIA .7 .795
48 BELIZE .69 .778
49 CYPRUS .69 .903
50 ITALY .69 .941
51 MEXICO .69 .829
52 SINGAPORE .69 .922
53 SOLOMONISLANDS .69 .602
54 TRINIDADANDTOBAGO .69 .814
55 ARGENTINA .68 .869
56 FIJI .67 .762
57 ISRAEL .67 .932
58 MONGOLIA .67 .7
59 SAOTOMEANDPRINCIPE .67 .654
60 ELSALVADOR .66 .735
61 FRANCE .66 .952
62 HONGKONG .66 .937
63 INDONESIA .66 .728
64 KYRGYZSTAN .66 .696
65 MALDIVES .66 .741
66 SLOVENIA .66 .917
67 TAIWAN .66 .925
68 EASTTIMOR .66 .514
69 TONGA .66 .819
70 CHILE .65 .867
71 GRENADA .65 .777
72 MAURITIUS .65 .804
73 NAMIBIA .65 .65
74 PARAGUAY .65 .755
75 THAILAND .65 .781
76 CZECHREPUBLIC .64 .891
77 PHILIPPINES .64 .771
78 TUNISIA .64 .766
79 UZBEKISTAN .64 .702
80 BRAZIL .63 .8
81 CHINA .63 .777
82 CUBA .63 .838
83 GREECE .63 .926
84 NICARAGUA .63 .71
85 PAPUANEWGUINEA .63 .53
86 URUGUAY .63 .852
87 GABON .62 .677
88 GHANA .62 .553
89 JAPAN .62 .953
90 YEMEN .62 .508
91 PORTUGAL .61 .897
92 SRILANKA .61 .743
93 TAJIKISTAN .61 .673
94 VIETNAM .61 .733
95 IRAN .6 .759
96 COMOROS .59 .561
97 CROATIA .59 .85
98 POLAND .59 .87
99 CAPEVERDE .58 .736
100 KAZAKHSTAN .58 .794
101 MADAGASCAR .58 .533
102 SOUTHKOREA .58 .921
103 BANGLADESH .57 .547
104 CONGO .57 .548
105 GAMBIA .57 .502
106 HUNGARY .57 .874
107 LIBYA .57 .818
108 SOUTHAFRICA .57 .674
109 CAMBODIA .56 .598
110 ECUADOR .56 .772
111 KENYA .56 .521
112 LEBANON .56 .772
113 MOROCCO .56 .646
114 PERU .56 .773
115 SENEGAL .56 .499
116 BOLIVIA .55 .695
117 HAITI .55 .529
118 NEPAL .55 .534
119 NIGERIA .55 .47
120 TANZANIA .55 .467
121 BENIN .54 .437
122 BOTSWANA .54 .654
123 GUINEABISSAU .54 .374
124 INDIA .54 .619
125 LAOS .54 .601
126 MOZAMBIQUE .54 .384
127 PALESTINE .54 .731
128 SLOVAKIA .54 .863
129 BURMA .53 .583
130 MALI .53 .38
131 MAURITANIA .53 .55
132 TURKEY .53 .775
133 ALGERIA .52 .733
134 EQUATORIALGUINEA .52 .642
135 ROMANIA .52 .813
136 BOSNIAANDHERZEGOVENIA .51 .803
137 CAMEROON .51 .532
138 ESTONIA .51 .86
139 GUINEA .51 .456
140 JORDAN .51 .773
141 SYRIA .51 .724
142 SIERRALEONE .5 .336
143 AZERBAIJAN .49 .746
144 CENTRALAFRICANREPUBLIC .49 .384
145 MACEDONIA .49 .801
146 TOGO .49 .512
147 ZAMBIA .49 .434
148 ANGOLA .48 .446
149 DJIBOUTI .48 .516
150 EGYPT .48 .708
151 BURKINAFASO .47 .37
152 ETHIOPIA .47 .406
153 LATVIA .47 .855
154 LITHUANIA .47 .862
155 UGANDA .47 .505
156 ALBANIA .46 .801
157 MALAWI .46 .437
158 CHAD .45 .388
159 IVORYCOAST .45 .432
160 NIGER .45 .374
161 ERITREA .44 .483
162 RWANDA .44 .452
163 BULGARIA .43 .824
164 LESOTHO .43 .549
165 PAKISTAN .43 .551
166 RUSSIA .43 .802
167 SWAZILAND .42 .547
168 GEORGIA .41 .745
169 BELARUS .4 .804
170 TURKMENISTAN .4 .713
171 ARMENIA .37 .775
172 SUDAN .36 .526
173 UKRAINE .36 .788
174 MOLDOVA .35 .708
175 ZAIRE .33 .411
176 ZIMBABWE .33 .513
177 BURUNDI .3
178 .413
country <- HDISWLSdata[,1]
SWLS <- HDISWLSdata[,2]
HDI <- HDISWLSdata[,2]
HDI <- HDISWLSdata[,3]
country
[1] DENMARK SWITZERLAND AUSTRIA
ICELAND
[5] BAHAMAS FINLAND SWEDEN
BHUTAN
[9] BRUNEIDARUSSALAM CANADA IRELAND
LUXEMBOURG
[13] COSTARICA MALTA NETHERLANDS
ANTIGUAANDBARBUDA
[17] MALAYSIA NEWZEALAND NORWAY
SEYCHELLES
[21] STKITTSANDNEVIS UAE USA
VANUATU
[25] VENEZUELA AUSTRALIA BARBADOS
BELGIUM
[29] DOMINICA OMAN SAUDIARABIA
SURINAME
[33] BAHRAIN COLUMBIA GERMANY
GUYANA
[37] HONDURAS KUWAIT PANAMA
STVINCENTANDTHEGRENADINES
[41] UNITEDKINGDOM DOMINICANREPUBLIC GUATEMALA
JAMAICA
[45] QATAR SPAIN STLUCIA
BELIZE
[49] CYPRUS ITALY MEXICO
SINGAPORE
[53] SOLOMONISLANDS TRINIDADANDTOBAGO ARGENTINA
FIJI
[57] ISRAEL MONGOLIA SAOTOMEANDPRINCIPE
ELSALVADOR
[61] FRANCE HONGKONG INDONESIA
KYRGYZSTAN
[65] MALDIVES SLOVENIA TAIWAN
EASTTIMOR
[69] TONGA CHILE GRENADA
MAURITIUS
[73] NAMIBIA PARAGUAY THAILAND
CZECHREPUBLIC
[77] PHILIPPINES TUNISIA UZBEKISTAN
BRAZIL
[81] CHINA CUBA GREECE
NICARAGUA
[85] PAPUANEWGUINEA URUGUAY GABON
GHANA
[89] JAPAN YEMEN PORTUGAL
SRILANKA
[93] TAJIKISTAN VIETNAM IRAN
COMOROS
[97] CROATIA POLAND CAPEVERDE
KAZAKHSTAN
[101] MADAGASCAR SOUTHKOREA BANGLADESH
CONGO
[105] GAMBIA HUNGARY LIBYA
SOUTHAFRICA
[109] CAMBODIA ECUADOR KENYA
LEBANON
[113] MOROCCO PERU SENEGAL
BOLIVIA
[117] HAITI NEPAL NIGERIA
TANZANIA
[121] BENIN BOTSWANA GUINEABISSAU
INDIA
[125] LAOS MOZAMBIQUE PALESTINE
SLOVAKIA
[129] BURMA MALI MAURITANIA
TURKEY
[133] ALGERIA EQUATORIALGUINEA ROMANIA
BOSNIAANDHERZEGOVENIA
[137] CAMEROON ESTONIA GUINEA
JORDAN
[141] SYRIA SIERRALEONE AZERBAIJAN
CENTRALAFRICANREPUBLIC
[145] MACEDONIA TOGO ZAMBIA
ANGOLA
[149] DJIBOUTI EGYPT BURKINAFASO
ETHIOPIA
[153] LATVIA LITHUANIA UGANDA
ALBANIA
[157] MALAWI CHAD IVORYCOAST
NIGER
[161] ERITREA RWANDA BULGARIA
LESOTHO
[165] PAKISTAN RUSSIA SWAZILAND
GEORGIA
[169] BELARUS TURKMENISTAN ARMENIA
SUDAN
[173] UKRAINE MOLDOVA ZAIRE
ZIMBABWE
[177] BURUNDI
178 Levels: ALBANIA ALGERIA ANGOLA ANTIGUAANDBARBUDA ARGENTINA ARMENIA
AUSTRALIA AUSTRIA AZERBAIJAN BAHAMAS ... ZIMBABWE
SWLS
[1] .82 .82 .78 .78 .77 .77 .77 .76 .76 .76 .76 .76 .75 .75 .75 .74 .74 .74
.74 .74 .74 .74 .74 .74 .74 .73 .73 .73 .73
[30] .73 .73 .73 .72 .72 .72 .72 .72 .72 .72 .72 .71 .7 .7 .7 .7 .7 .7
.69 .69 .69 .69 .69 .69 .69 .68 .67 .67 .67
[59] .67 .66 .66 .66 .66 .66 .66 .66 .66 .66 .66 .65 .65 .65 .65 .65 .65 .64
.64 .64 .64 .63 .63 .63 .63 .63 .63 .63 .62
[88] .62 .62 .62 .61 .61 .61 .61 .6 .59 .59 .59 .58 .58 .58 .58 .57 .57 .57
.57 .57 .57 .56 .56 .56 .56 .56 .56 .56 .55
[117] .55 .55 .55 .55 .54 .54 .54 .54 .54 .54 .54 .54 .53 .53 .53 .53 .52 .52
.52 .51 .51 .51 .51 .51 .51 .5 .49 .49 .49
[146] .49 .49 .48 .48 .48 .47 .47 .47 .47 .47 .46 .46 .45 .45 .45 .44 .44 .43
.43 .43 .43 .42 .41 .4 .4 .37 .36 .36 .35
[175] .33 .33 .3
46 Levels: .3 .33 .35 .36 .37 .4 .41 .42 .43 .44 .45 .46 .47 .48 .49 .5 .51
.52 .53 .54 .55 .56 .57 .58 .59 .6 ... .82
HDI
[1] .949 .955 .948 .968 .845 .952 .956 .579 .894 .961 .959 .944 .846 .878 .953
.815 .811 .943 .968 .843 .821 .868 .951
[24] .674 .792 .962 .892 .946 .798 .814 .812 .774 .866 .791 .935 .75 .7 .891
.812 .761 .946 .779 .689 .736 .875 .949
[47] .795 .778 .903 .941 .829 .922 .602 .814 .869 .762 .932 .7 .654 .735 .952
.937 .728 .696 .741 .917 .925 .514 .819
[70] .867 .777 .804 .65 .755 .781 .891 .771 .766 .702 .8 .777 .838 .926 .71
.53 .852 .677 .553 .953 .508 .897 .743
[93] .673 .733 .759 .561 .85 .87 .736 .794 .533 .921 .547 .548 .502 .874 .818
.674 .598 .772 .521 .772 .646 .773 .499
[116] .695 .529 .534 .47 .467 .437 .654 .374 .619 .601 .384 .731 .863 .583 .38
.55 .775 .733 .642 .813 .803 .532 .86
[139] .456 .773 .724 .336 .746 .384 .801 .512 .434 .446 .516 .708 .37 .406 .855
.862 .505 .801 .437 .388 .432 .374 .483
[162] .452 .824 .549 .551 .802 .547 .745 .804 .713 .775 .526 .788 .708 .411 .513
.413
154 Levels: .336 .37 .374 .38 .384 .388 .406 .411 .413 .432 .434 .437 .446
.452 .456 .467 .47 .483 .499 .502 ... .968
lm(SWLS ~ HDI)
Error in storage.mode(y) <- "double" :
invalid to change the storage mode of a factor
In addition: Warning message:
In model.response(mf, "numeric") :
using type="numeric" with a factor response will be ignored
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Thomas Lumley Assoc. Professor, Biostatistics
tlum...@u.washington.edu University of Washington, Seattle
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