Thank you for giving this some thought Joshua.  I will be sure to keep
troubleshooting this as well.  Would it be related to how gls calculates
its values that is somehow reports the 'correct' F value perhaps?

Regards,
Charles

On Mon, May 21, 2012 at 11:08 AM, Joshua Wiley <jwiley.psych@gmail.com>wrote:

> That suggests they are fitting different models somehow (not just that
> the specifc effect estimates are different).  No brilliant ideas on in
> what way though...
>
> I checked REML versus ML but that was not it.  I'll let you know if I
> have any ideas.
>
> Cheers,
>
> Josh
>
> On Mon, May 21, 2012 at 9:02 AM, Charles Determan Jr <deter088@umn.edu>
> wrote:
> > Hi Joshua,
> >
> > The -2 Log-likelihood from SAS is -58.6
> > The log-likelihood from R fit.13 is 21.9.  I assume this would be
> multiplied
> > by -2 which would give -43.8.
> >
> > Regards,
> > Charles
> >
> >
> > On Mon, May 21, 2012 at 10:02 AM, Joshua Wiley <jwiley.psych@gmail.com>
> > wrote:
> >>
> >> Hi Charles,
> >>
> >> Out of curiosity, what is the log likelihood from SAS?  Does it match
> >> that from lme()?
> >>
> >> logLik(fit.13)
> >>
> >> will give it to you.
> >>
> >> Cheers,
> >>
> >> Josh
> >>
> >> On Mon, May 21, 2012 at 5:45 AM, Charles Determan Jr <deter088@umn.edu>
> >> wrote:
> >> > Greetings R users,
> >> >
> >> >
> >> > I am trying to match some SAS output of a mixed model.  After running
> >> > PROC
> >> > MIXED with the covariance structure as AR1 the output below is given.
> >> >  Now
> >> > when I try to replicate this with lme, I get the correct degrees of
> >> > freedom
> >> > and somewhat close values.  If I try with gls, I get the exact F value
> >> > but
> >> > the incorrect denominator degrees of freedom.  Is there some syntax or
> >> > parameter I can adjust to get lme to have the same F values as gls?
> >> >  That
> >> > way the correct degrees of freedom would be applied and I would get
> the
> >> > replicated model.  The data is also included below.  Thanks to any who
> >> > can
> >> > help with this issue.
> >> >
> >> >
> >> > Regards,
> >> >
> >> > Charles
> >> >
> >> >
> >> > Row   ID Group Died Event_name      var
> >> > 1    12510     3  YES          B     -1.05257
> >> > 2    12510     3  YES        S45    -1.00000
> >> > 3    12510     3  YES        FR2   -1.14630
> >> > 4    12510     3  YES        FR8   -1.08831
> >> > 5    12510     3  YES       FR20   -1.03339
> >> > 6    21510     3   NO          B      -0.87290
> >> > 7    21510     3   NO        S45     -1.22185
> >> > 8    21510     3   NO        FR2     -1.01592
> >> > 9    21510     3   NO        FR8    -1.06550
> >> > 10   21510     3   NO       PR48    -0.65326
> >> > 11   22210     3  YES          B     -1.37059
> >> > 12   30810     3   NO          B     -0.92959
> >> > 13   30810     3   NO        S45    -1.26680
> >> > 14   30810     3   NO        FR2    -0.99396
> >> > 15   30810     3   NO        FR8    -1.04769
> >> > 16   30810     3   NO       FR20    -1.04769
> >> > 17   31510     4  YES          B     -1.50585
> >> > 18   31510     4  YES        S45    -1.35262
> >> > 19   31510     4  YES        FR2   -1.26520
> >> > 20   31510     4  YES        FR8    -1.11407
> >> > 21   31510     4  YES       FR20    -0.97757
> >> > 22   40510     2  YES          B      -1.04721
> >> > 23   40510     2  YES        S45     -1.13371
> >> > 24   51010     3   NO          B        -1.21467
> >> > 25   51010     3   NO        S45      -1.18177
> >> > 26   51010     3   NO        FR2     -1.23582
> >> > 27   51010     3   NO        FR8     -1.35262
> >> > 28   51010     3   NO       FR20    -0.69897
> >> > 29   51010     3   NO       PR48    -1.14086
> >> > 30   51710     4   NO          B      -1.13371
> >> > 31   51710     4   NO        S45     -1.24336
> >> > 32   51710     4   NO        FR2     -0.85201
> >> > 33   51710     4   NO        FR8     -0.72700
> >> > 34   51710     4   NO       FR20     -0.71220
> >> > 35   51710     4   NO       PR48     -1.10735
> >> > 36   51809     1   NO          B         -0.70752
> >> > 37   51809     1   NO        FR2     -0.58120
> >> > 38   51809     1   NO        FR8     -0.71332
> >> > 39   51809     1   NO       FR20     -0.37212
> >> > 40   61410     4   NO          B     -1.25493
> >> > 41   61410     4   NO        S45     -1.24949
> >> > 42   61410     4   NO        FR2     -1.18310
> >> > 43   61410     4   NO        FR8     -0.87517
> >> > 44   61410     4   NO       FR20     -0.34679
> >> > 45   61410     4   NO       PR48     -0.76472
> >> > 46   62110     3   NO          B         -1.34199
> >> > 47   62110     3   NO        S45     -1.23657
> >> > 48   62110     3   NO        FR2     -1.20412
> >> > 49   62110     3   NO        FR8     -0.72011
> >> > 50   62110     3   NO       FR20     -0.72308
> >> > 51   62110     3   NO       PR48     -0.89688
> >> > 52   62209     3   NO          B         -0.74041
> >> > 53   62209     3   NO        S45     -0.99183
> >> > 54   62209     3   NO        FR2     -1.06854
> >> > 55   62209     3   NO        FR8     -0.94386
> >> > 56   62209     3   NO       FR20     -0.38817
> >> > 57   71210     4  YES          B     -1.23657
> >> > 58   71210     4  YES        S45     -0.94808
> >> > 59   71309     4  YES          B     -1.14630
> >> > 60   71309     4  YES        S45     -1.10568
> >> > 61   71309     4  YES        FR2     -0.94462
> >> > 62   71309     4  YES        FR8     -0.89211
> >> > 63   71309     4  YES       FR20     -0.98970
> >> > 64   71309     4  YES       PR48     -0.83387
> >> > 65   81009     4  YES          B         -1.15989
> >> > 66   81009     4  YES        S45     -0.93779
> >> > 67   81009     4  YES        FR2     -0.86710
> >> > 68   81009     4  YES        FR8     -0.69379
> >> > 69   81610     1   NO          B         -1.04769
> >> > 70   81610     1   NO        S45     -1.02780
> >> > 71   81610     1   NO        FR2     -0.96098
> >> > 72   81610     1   NO        FR8     -0.91829
> >> > 73   81610     1   NO       FR20     -0.68550
> >> > 74   81610     1   NO       PR48     -0.66374
> >> > 75   81709     4  YES          B    -0.65521
> >> > 76   82410     3   NO          B     -1.06702
> >> > 77   82410     3   NO        S45     -1.30103
> >> > 78   82410     3   NO        FR2     -0.96617
> >> > 79   82410     3   NO        FR8     -0.84497
> >> > 80   82410     3   NO       FR20     -0.47716
> >> > 81   82410     3   NO       PR48     -0.68131
> >> > 82   91310     4   NO          B         -1.30803
> >> > 83   91310     4   NO        S45     -1.07212
> >> > 84   91310     4   NO        FR2     -0.94615
> >> > 85   91310     4   NO        FR8     -1.29414
> >> > 86   91310     4   NO       FR20     -0.81304
> >> > 87   91310     4   NO       PR48     -0.86519
> >> > 88   91409     4   NO          B         -1.12321
> >> > 89   91409     4   NO        S45     -1.08831
> >> > 90   91409     4   NO        FR2     -1.11862
> >> > 91   91409     4   NO        FR8     -0.87976
> >> > 92   91409     4   NO       FR20     -0.87517
> >> > 93   91409     4   NO       PR48     -0.68867
> >> > 94   92109     3   NO          B         -1.15120
> >> > 95   92109     3   NO        S45     -0.99525
> >> > 96   92109     3   NO        FR2     -0.95429
> >> > 97   92109     3   NO        FR8     -0.54914
> >> > 98   92109     3   NO       FR20     -0.67264
> >> > 99   92109     3   NO       PR48     -0.74256
> >> > 100  92110     4  YES          B     -1.05012
> >> > 101  92110     4  YES        S45     -1.14086
> >> > 102  92110     4  YES        FR2     -0.91901
> >> > 103  92110     4  YES        FR8     -0.80521
> >> > 104  92110     4  YES       FR20     -0.88807
> >> > 105  92710     4   NO          B         -1.20412
> >> > 106  92710     4   NO        S45     -1.21325
> >> > 107  92710     4   NO        FR2     -1.19518
> >> > 108  92710     4   NO        FR8     -0.92959
> >> > 109  92710     4   NO       FR20     -0.69315
> >> > 110  92710     4   NO       PR48     -0.73779
> >> > 111 100410     1   NO          B         -0.92300
> >> > 112 100410     1   NO        S45     -1.07314
> >> > 113 100410     1   NO        FR2     -0.80162
> >> > 114 100410     1   NO        FR8     -0.63283
> >> > 115 100410     1   NO       FR20     -0.73119
> >> > 116 100410     1   NO       PR48      0.10102
> >> > 117 101209     3   NO          B     -1.24718
> >> > 118 101209     3   NO        S45     -1.00524
> >> > 119 101209     3   NO        FR2     -1.01592
> >> > 120 101209     3   NO        FR8     -0.85201
> >> > 121 101209     3   NO       FR20     -0.51670
> >> > 122 101209     3   NO       PR48     -0.72239
> >> > 123 101909     3   NO          B         -1.13549
> >> > 124 101909     3   NO        S45     -0.92665
> >> > 125 101909     3   NO        FR2     -0.98548
> >> > 126 101909     3   NO        FR8     -1.03152
> >> > 127 101909     3   NO       FR20     -0.71715
> >> > 128 101909     3   NO       PR48     -1.07935
> >> > 129 102510     2  YES          B         -1.30103
> >> > 130 102510     2  YES        S45     -0.83387
> >> > 131 110810     3  YES          B     -1.21968
> >> > 132 110810     3  YES        S45     -0.68048
> >> > 133 110810     3  YES        FR2     -1.09474
> >> > 134 110909     2  YES          B         -1.09259
> >> > 135 110909     2  YES        S45     -0.91293
> >> > 136 111510     3   NO          B         -1.39794
> >> > 137 111510     3   NO        S45     -1.42366
> >> > 138 111510     3   NO        FR2     -1.22621
> >> > 139 111510     3   NO        FR8     -0.98885
> >> > 140 111510     3   NO       FR20     -0.66055
> >> > 141 111510     3   NO       PR48     -0.84497
> >> > 142 111609     1   NO          B         -0.79942
> >> > 143 111609     1   NO        S45     -0.87517
> >> > 144 111609     1   NO        FR2     -0.74041
> >> > 145 111609     1   NO        FR8     -0.64092
> >> > 146 111609     1   NO       FR20     -0.53835
> >> > 147 111609     1   NO       PR48     -0.68719
> >> > 148 120610     4   NO          B     -1.05110
> >> > 149 120610     4   NO        S45     -1.45100
> >> > 150 120610     4   NO        FR2     -1.21183
> >> > 151 120610     4   NO        FR8     -1.04144
> >> > 152 120610     4   NO       FR20     -0.61101
> >> > 153 120610     4   NO       PR48     -0.81702
> >> > 154 120709     1   NO          B         -0.84497
> >> > 155 120709     1   NO        S45     -0.99439
> >> > 156 120709     1   NO        FR2     -1.13430
> >> > 157 120709     1   NO       FR20     -0.57187
> >> > 158 120709     1   NO       PR48     -0.80632
> >> > 159 121310     3  YES          B         -1.16115
> >> > 160 121310     3  YES        S45     -1.18310
> >> >
> >> > dat=read.table("C:/…/subset.csv",sep=",",header=TRUE, na.strings=".")
> >> >
> >> > attach(dat)
> >> >
> >> >
> >> >
> >> > dat34=dat[Pig_group %in% c("3", "4"),]
> >> >
> >> > attach(dat34)
> >> >
> >> > dat34=within(dat34, {
> >> >
> >> >                    group=factor(group)
> >> >
> >> >                    Event_name=factor(Event_name)
> >> >
> >> >                    Died=factor(Died)
> >> >
> >> >                    ID=factor(ID)
> >> >
> >> > })
> >> >
> >> > attach(dat34)
> >> >
> >> >
> >> >
> >> > contrasts(dat34$Event_name)=contr.sum(n=6)
> >> >
> >> > contrasts(dat34$group)=contr.sum(n=2)
> >> >
> >> > contrasts(dat34$Died)=contr.sum(n=2)
> >> >
> >> >
> >> >  # What the results should be from SAS AR1 var
> >> > #Type 3 Tests of Fixed Effects
> >> > #Effect          NumDF DenDF F Value Pr > F
> >> > #Event_name      5   91    7.43    <.0001
> >> > #Died              1   24    0.08    0.7756
> >> > #Event_name*Died 5   91    3.09    0.0128
> >> >
> >> > fit.13=lme(var~Event_name*Died,
> >> >    data=liver34,
> >> >    random=~1|ID,
> >> >    corr=corAR1())
> >> > anova(fit.13, type="marginal", adjustSigma=F)
> >> > #                    numDF denDF   F-value p-value
> >> > #(Intercept)             1    91 1342.7364  <.0001
> >> > #Event_name          5    91    8.7143  <.0001
> >> > #Died                    1    24    0.0527  0.8204
> >> > #Event_name:Died     5    91    3.0909  0.0127
> >> >
> >> > ######################################################
> >> > ###THIS DOES IT but not lme function (need dfs)
> >> > fit.16=gls(var~Event_name*Died,
> >> >    data=liver34,
> >> >    corr=corAR1(, ~1|ID))
> >> > anova(fit.16, type="marginal", adjustSigma=F)
> >> > #Denom. DF: 115
> >> > #                    numDF   F-value p-value
> >> > #(Intercept)             1 1496.9032  <.0001
> >> > #Event_name          5    7.4304  <.0001
> >> > #Died                    1    0.0831  0.7736
> >> > #Event_name:Died     5    3.0871  0.0119
> >> >
> >> >  #Give exact replicated answers
> >> > 1-pf(7.4304, 5, 91)
> >> > 1-pf(.0831, 1, 24)
> >> > 1-pf(3.0871, 5, 91)
> >> > #######################################################
> >> >
> >> >        [[alternative HTML version deleted]]
> >> >
> >> >
> >> > _______________________________________________
> >> > R-sig-mixed-models@r-project.org mailing list
> >> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >> >
> >>
> >>
> >>
> >> --
> >> Joshua Wiley
> >> Ph.D. Student, Health Psychology
> >> Programmer Analyst II, Statistical Consulting Group
> >> University of California, Los Angeles
> >> https://joshuawiley.com/
> >
> >
>
>
>
> --
> Joshua Wiley
> Ph.D. Student, Health Psychology
> Programmer Analyst II, Statistical Consulting Group
> University of California, Los Angeles
> https://joshuawiley.com/
>

	[[alternative HTML version deleted]]

