[R] ML Estimation Differences with R and SAS

From: Patrick Richardson <xplaner800_at_comcast.net>
Date: Mon, 10 Mar 2008 13:09:06 -0400


List,

I'm working on fitting a logistic model for a well known dataset (which is given below in case anyone wants to try to reproduce). I used both R and SAS to fit the model and have some differences in the parameter estimates. I'm wondering if R calculates the ML estimates differently. I'm making NO accusations as to which program is "right or wrong". That is not the focus of this posting. As a "newer" R user I'm trying to understand the algorithm that R might use to calculate ML estimation. The largest difference seems to with the race factors. R gives a p-value of 0.46995 for race=black and SAS gives a p-value of 0.0753 for race=black. Clearly one is borderline significant and the other is not. Many thanks to all who might be able to offer any insight on this. Both R and SAS code and output are included in this message (along with the dataset).

Thanks,

Patrick

MY R CODE IS: Dataset <- read.table("<path>", header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE)
Dataset$race <- factor(Dataset$race, levels=c('other','black','white'))
GLM.1 <- glm(low ~ lwt + ptl + ht + race + smoke , family=binomial(logit), data=Dataset)
summary(GLM.1)

MY SAS CODE IS: PROC LOGISTIC descending DATA=p2;
class race (ref='other');
MODEL LOW = lwt ptl ht race smoke / lackfit parmlabel expb link=logit; RUN; MY R OUTPUT IS: Coefficients:

              Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.92619 0.85549 1.083 0.27897

lwt           -0.01650    0.00692  -2.384  0.01712 * 
ptl            1.23116    0.44607   2.760  0.00578 **
ht             1.76197    0.70748   2.490  0.01276 * 
race[T.black]  0.39552    0.54739   0.723  0.46995   
race[T.white] -0.86291    0.43517  -1.983  0.04737 * 
smoke          0.88007    0.40049   2.197  0.02798 * 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 


(Dispersion parameter for binomial family taken to be 1)
Null deviance: 234.67 on 188 degrees of freedom Residual deviance: 200.62 on 182 degrees of freedom AIC: 214.62 Number of Fisher Scoring iterations: 4 MY SAS OUTPUT IS: The LOGISTIC Procedure Analysis of Maximum Likelihood Estimates Standard Wald Parameter DF Estimate Error Chi-Square Pr > ChiSq Exp(Est) Label Intercept 1 0.9287 0.9326 0.9916 0.3193 2.531 Intercept: low=1 lwt 1 -0.0173 0.00699 6.1425 0.0132 0.983 ptl 1 1.1958 0.4472 7.1493 0.0075 3.306 ht 1 1.7482 0.7090 6.0805 0.0137 5.745 race black 1 0.5963 0.3352 3.1643 0.0753 1.815 race black race white 1 -0.7200 0.2668 7.2803 0.0070 0.487 race white smoke 1 0.8648 0.4009 4.6534 0.0310 2.375 0 19 182 black 0 0 1 0 0 2523 0 33 155 other 0 0 0 1 0 2551 0 20 105 white 1 0 0 1 0 2557 0 21 108 white 1 0 1 1 0 2594 0 18 107 white 1 0 1 0 0 2600 0 21 124 other 0 0 0 0 0 2622 0 22 118 white 0 0 0 1 0 2637 0 17 103 other 0 0 0 1 0 2637 0 29 123 white 1 0 0 1 0 2663 0 26 113 white 1 0 0 0 0 2665 0 19 95 other 0 0 0 0 0 2722 0 19 150 other 0 0 0 1 0 2733 0 22 95 other 0 1 0 0 0 2750 0 30 107 other 0 0 1 1 1 2750 0 18 100 white 1 0 0 0 0 2769 0 15 98 black 0 0 0 0 0 2778 0 25 118 white 1 0 0 1 0 2782 0 20 120 other 0 0 1 0 0 2807 0 28 120 white 1 0 0 1 0 2821 0 32 101 other 0 0 0 1 0 2835 0 31 100 white 0 0 1 1 0 2835 0 36 202 white 0 0 0 1 0 2836 0 28 120 other 0 0 0 0 0 2863 0 25 120 other 0 0 1 1 0 2877 0 28 167 white 0 0 0 0 0 2877 0 17 122 white 1 0 0 0 0 2906 0 29 150 white 0 0 0 1 0 2920 0 26 168 black 1 0 0 0 0 2920 0 17 113 black 0 0 0 1 0 2920 0 24 90 white 1 0 0 1 1 2948 0 35 121 black 1 0 0 1 1 2948 0 25 155 white 0 0 0 1 0 2977 0 25 125 black 0 0 0 0 0 2977 0 29 140 white 1 0 0 1 0 2977 0 19 138 white 1 0 0 1 0 2977 0 27 124 white 1 0 0 0 0 2992 0 31 215 white 1 0 0 1 0 3005 0 33 109 white 1 0 0 1 0 3033 0 21 185 black 1 0 0 1 0 3042 0 19 189 white 0 0 0 1 0 3062 0 23 130 black 0 0 0 1 0 3062 0 21 160 white 0 0 0 0 0 3062 0 18 90 white 1 0 1 0 0 3076 0 18 90 white 1 0 1 0 0 3076 0 32 132 white 0 0 0 1 0 3080 0 19 132 other 0 0 0 0 0 3090 0 24 115 white 0 0 0 1 0 3090 0 22 85 other 1 0 0 0 0 3090 0 22 120 white 0 1 0 1 0 3100 0 23 128 other 0 0 0 0 0 3104 0 22 130 white 1 0 0 0 0 3132 0 30 95 white 1 0 0 1 0 3147 0 19 115 other 0 0 0 0 0 3175 0 16 110 other 0 0 0 0 0 3175 0 21 110 other 1 0 1 0 0 3203 0 30 153 other 0 0 0 0 0 3203 0 20 103 other 0 0 0 0 0 3203 0 17 119 other 0 0 0 0 0 3225 0 23 119 other 0 0 0 1 0 3232 0 24 110 other 0 0 0 0 0 3232 0 28 140 white 0 0 0 0 0 3234 0 26 133 other 1 0 0 0 1 3260 0 20 169 other 0 0 1 1 1 3274 0 24 115 other 0 0 0 1 0 3274 0 28 250 other 1 0 0 1 0 3303 0 20 141 white 0 0 1 1 1 3317 0 22 158 black 0 0 0 1 1 3317 0 22 112 white 1 0 0 0 1 3317 0 31 150 other 1 0 0 1 0 3321 0 23 115 other 1 0 0 1 0 3331 0 16 112 black 0 0 0 0 0 3374 0 16 135 white 1 0 0 0 0 3374 0 18 229 black 0 0 0 0 0 3402 0 25 140 white 0 0 0 1 0 3416 0 32 134 white 1 0 0 1 1 3430 0 20 121 black 1 0 0 0 0 3444 0 23 190 white 0 0 0 0 0 3459 0 22 131 white 0 0 0 1 0 3460 0 32 170 white 0 0 0 0 0 3473 0 30 110 other 0 0 0 0 0 3475 0 20 127 other 0 0 0 0 0 3487 0 23 123 other 0 0 0 0 0 3544 0 17 120 other 1 0 0 0 0 3572 0 19 105 other 0 0 0 0 0 3572 0 23 130 white 0 0 0 0 0 3586 0 36 175 white 0 0 0 0 0 3600 0 22 125 white 0 0 0 1 0 3614 0 24 133 white 0 0 0 0 0 3614 0 21 134 other 0 0 0 1 0 3629 0 19 235 white 1 1 0 0 0 3629 0 25 95 white 1 0 1 0 1 3637 0 16 135 white 1 0 0 0 0 3643 0 29 135 white 0 0 0 1 0 3651 0 29 154 white 0 0 0 1 0 3651 0 19 147 white 1 0 0 0 0 3651 0 19 147 white 1 0 0 0 0 3651 0 30 137 white 0 0 0 1 0 3699 0 24 110 white 0 0 0 1 0 3728 0 19 184 white 1 1 0 0 0 3756 0 24 110 other 0 0 0 0 1 3770 0 23 110 white 0 0 0 1 0 3770 0 20 120 other 0 0 0 0 0 3770 0 25 241 black 0 1 0 0 0 3790 0 30 112 white 0 0 0 1 0 3799 0 22 169 white 0 0 0 0 0 3827 0 18 120 white 1 0 0 1 0 3856 0 16 170 black 0 0 0 1 0 3860 0 32 186 white 0 0 0 1 0 3860 0 18 120 other 0 0 0 1 0 3884 0 29 130 white 1 0 0 1 0 3884 0 33 117 white 0 0 1 1 0 3912 0 20 170 white 1 0 0 0 0 3940 0 28 134 other 0 0 0 1 0 3941 0 14 135 white 0 0 0 0 0 3941 0 28 130 other 0 0 0 0 0 3969 0 25 120 white 0 0 0 1 0 3983 0 16 95 other 0 0 0 1 0 3997 0 20 158 white 0 0 0 1 0 3997 0 26 160 other 0 0 0 0 0 4054 0 21 115 white 0 0 0 1 0 4054 0 22 129 white 0 0 0 0 0 4111 0 25 130 white 0 0 0 1 0 4153 0 31 120 white 0 0 0 1 0 4167 0 35 170 white 0 0 0 1 1 4174 0 19 120 white 1 0 0 0 0 4238 0 24 116 white 0 0 0 1 0 4593 0 45 123 white 0 0 0 1 0 4990 1 28 120 other 1 0 1 0 1 709 1 29 130 white 0 0 1 1 0 1021 1 34 187 black 1 1 0 0 0 1135 1 25 105 other 0 1 0 0 1 1330 1 25 85 other 0 0 1 0 0 1474 1 27 150 other 0 0 0 0 0 1588 1 23 97 other 0 0 1 1 0 1588 1 24 124 black 0 0 0 1 1 1701 1 24 132 other 0 1 0 0 0 1729 1 21 165 white 1 1 0 1 0 1790 1 32 105 white 1 0 0 0 0 1818 1 19 91 white 1 0 1 0 1 1885 1 25 115 other 0 0 0 0 0 1893 1 16 130 other 0 0 0 1 0 1899 1 25 92 white 1 0 0 0 0 1928 1 20 150 white 1 0 0 1 0 1928 1 21 200 black 0 0 1 1 0 1928 1 24 155 white 1 0 0 0 1 1936 1 21 103 other 0 0 0 0 0 1970 1 20 125 other 0 0 1 0 0 2055 1 25 89 other 0 0 0 1 1 2055 1 19 102 white 0 0 0 1 0 2082 1 19 112 white 1 0 1 0 0 2084 1 26 117 white 1 0 0 0 1 2084 1 24 138 white 0 0 0 0 0 2100 1 17 130 other 1 0 1 0 1 2125 1 20 120 black 1 0 0 1 0 2126 1 22 130 white 1 0 1 1 1 2187 1 27 130 black 0 0 1 0 0 2187 1 20 80 other 1 0 1 0 0 2211 1 17 110 white 1 0 0 0 0 2225 1 25 105 other 0 0 0 1 1 2240 1 20 109 other 0 0 0 0 0 2240 1 18 148 other 0 0 0 0 0 2282 1 18 110 black 1 0 0 0 1 2296 1 20 121 white 1 0 1 0 1 2296 1 21 100 other 0 0 0 1 1 2301 1 26 96 other 0 0 0 0 0 2325 1 31 102 white 1 0 0 1 1 2353 1 15 110 white 0 0 0 0 0 2353 1 23 187 black 1 0 0 1 0 2367 1 20 122 black 1 0 0 0 0 2381 1 24 105 black 1 0 0 0 0 2381 1 15 115 other 0 0 1 0 0 2381 1 23 120 other 0 0 0 0 0 2395 1 30 142 white 1 0 0 0 1 2410 1 22 130 white 1 0 0 1 0 2410 1 17 120 white 1 0 0 1 0 2414 1 23 110 white 1 0 0 0 1 2424 1 17 120 black 0 0 0 1 0 2438 1 26 154 other 0 1 0 1 1 2442 1 20 105 other 0 0 0 1 0 2450 1 26 190 white 1 0 0 0 0 2466 1 14 101 other 1 0 0 0 1 2466 1 28 95 white 1 0 0 1 0 2466 1 14 100 other 0 0 0 1 0 2495 1 23 94 other 1 0 0 0 0 2495 1 17 142 black 0 1 0 0 0 2495 1 21 130 white 1 1 0 1 0 2495 ______________________________________________ R-help_at_r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Received on Mon 10 Mar 2008 - 17:13:03 GMT

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