Re: [R] lme4_0.995-2/Matrix_0.995-4 upgrade introduces error messages (change management)

From: White, Charles E WRAIR-Wash DC <charles.edwin.white_at_us.army.mil>
Date: Tue 31 Jan 2006 - 01:03:32 EST


I hope I'm not making your life unnecessarily difficult. As I will demonstrate below my signature, my original straight application of lme4_0.995-2/Matrix_0.995-4 is failing without providing any optimization information. For reference, I've provided optimization output from lme4_0.995-1/Matrix_0.995-1. Including the lmer command control=list(PQLmaxIt=0) or control=list(PQLmaxIt=10) produces exactly the same error as when the commands are not included.

Chuck

Charles E. White, Senior Biostatistician, MS Walter Reed Army Institute of Research
503 Robert Grant Ave., Room 1w102
Silver Spring, MD 20910-1557
301 319-9781

Personal/Professional Site:
http://users.starpower.net/cwhite571/professional/

> sessionInfo()
R version 2.2.1, 2005-12-20, i386-pc-mingw32

attached base packages:
[1] "methods" "stats" "graphics" "grDevices" "utils" "datasets"
[7] "base"

other attached packages:

     lme4 lattice Matrix
"0.995-2" "0.12-11" "0.995-4"
>
m1<-lmer(cbind(Treat.Landed,Control.Landed)~Repellant+Hour.After.Applica tion+(1|Volunteer)+(1|Date),
+ family=quasibinomial, method='Laplace') Error in glm.fit(X, Y, weights = weights, offset = offset, family = family, :

        NAs in V(mu)

########################################################################
##
> sessionInfo()
R version 2.2.1, 2005-12-20, i386-pc-mingw32

attached base packages:
[1] "methods" "stats" "graphics" "grDevices" "utils" "datasets"
[7] "base"

other attached packages:

     lme4 lattice Matrix
"0.995-1" "0.12-11" "0.995-1"
>
m1<-lmer(cbind(Treat.Landed,Control.Landed)~Repellant+Hour.After.Applica tion+(1|Volunteer)+(1|Date),
+ family=quasibinomial, method='Laplace')   EM iterations

  0 1643.816 ( 273.179: -0.0214) ( 90.3079: -0.0282)
  1 1640.765 ( 366.319: -0.0102) ( 248.902:-0.00169)
  2 1640.187 ( 437.442:-0.00561) ( 278.171:-0.000393)
  3 1639.953 ( 489.655:-0.00341) ( 285.979:-0.000160)
  4 1639.846 ( 527.983:-0.00221) ( 289.280:-9.04e-005)
  5 1639.793 ( 556.263:-0.00150) ( 291.184:-5.89e-005)
  6 1639.767 ( 577.229:-0.00105) ( 292.439:-4.07e-005)
  7 1639.753 ( 592.835:-0.000748) ( 293.311:-2.89e-005)
  8 1639.745 ( 604.485:-0.000541) ( 293.934:-2.09e-005)
  9 1639.741 ( 613.202:-0.000395) ( 294.386:-1.53e-005)
 10 1639.739 ( 619.736:-0.000291) ( 294.717:-1.12e-005)
 11 1639.738 ( 624.639:-0.000216) ( 294.961:-8.32e-006)
 12 1639.737 ( 628.322:-0.000161) ( 295.142:-6.19e-006)
 13 1639.736 ( 631.090:-0.000120) ( 295.277:-4.62e-006)
 14 1639.736 ( 633.172:-8.97e-005) ( 295.378:-3.46e-006)
 15 1639.736 ( 634.739:-6.72e-005) ( 295.453:-2.59e-006)
  0      1639.74: 0.00157545 0.00338463
  1      1639.74: 0.00156384 0.00338453
  2      1639.74: 0.00156308 0.00338224
  3      1639.74: 0.00156394 0.00338218
  4      1639.74: 0.00156367 0.00338136
  5      1639.74: 0.00156374 0.00338222
  6      1639.74: 0.00156367 0.00338219
  7      1639.74: 0.00156371 0.00338211
  8      1639.74: 0.00156366 0.00338206
  9      1639.74: 0.00156370 0.00338199
 10      1639.74: 0.00156370 0.00338199

  EM iterations
  0 1601.856 ( 639.508: 0.00108) ( 295.684: 0.00140)
  1 1601.814 ( 620.816:0.000875) ( 267.871:0.000262)
  2 1601.802 ( 606.495:0.000663) ( 263.248:6.65e-005)
  0      1601.80: 0.00164882 0.00379870
  1      1601.79: 0.00181161 0.00380177
  2      1601.79: 0.00176152 0.00395670
  3      1601.79: 0.00174046 0.00388111
  4      1601.79: 0.00176162 0.00387505
  5      1601.79: 0.00175271 0.00385493
  6      1601.79: 0.00176027 0.00385121
  7      1601.79: 0.00175618 0.00385019
  8      1601.79: 0.00175420 0.00384200
  9      1601.79: 0.00175615 0.00384174
 10      1601.79: 0.00175577 0.00383981
 11      1601.79: 0.00175577 0.00383981

  EM iterations
  0 1608.593 ( 569.550:-0.000323) ( 260.429:-0.000384)
  1 1608.591 ( 574.148:-0.000245) ( 267.114:-6.56e-005)
  2 1608.590 ( 577.686:-0.000179) ( 268.289:-1.70e-005)
  0      1608.59: 0.00173104 0.00372732
  1      1608.59: 0.00168995 0.00372648
  2      1608.59: 0.00170234 0.00368730
  3      1608.59: 0.00170328 0.00372838
  4      1608.59: 0.00170194 0.00372450
  5      1608.59: 0.00170465 0.00372141
  6      1608.59: 0.00170173 0.00371852
  7      1608.59: 0.00170315 0.00371466
  8      1608.59: 0.00170267 0.00371666
  9      1608.59: 0.00170246 0.00371667
 10      1608.59: 0.00170255 0.00371648

  EM iterations
  0 1608.661 ( 587.354:-6.52e-006) ( 269.072:-3.50e-006)
  1 1608.661 ( 587.452:-4.87e-006) ( 269.135:-7.21e-007)
  2 1608.661 ( 587.525:-3.58e-006) ( 269.148:-2.53e-007)
  0      1608.66: 0.00170206 0.00371543
  1      1608.66: 0.00170148 0.00371542
  2      1608.66: 0.00170148 0.00371524
  3      1608.66: 0.00170148 0.00371524
  4      1608.66: 0.00170148 0.00371524

  EM iterations
  0 1608.660 ( 587.724:-1.09e-008) ( 269.162:5.68e-008)
  1 1608.660 ( 587.724:-5.92e-009) ( 269.161:8.25e-009)
  2 1608.660 ( 587.724:-4.02e-009) ( 269.161:1.07e-009)
  0      1608.66: 0.00170148 0.00371525
  1      1608.66: 0.00170148 0.00371525
  2      1608.66: 0.00170148 0.00371525

  EM iterations
  0 1608.660 ( 587.725:2.30e-010) ( 269.161:4.40e-010)
  1 1608.660 ( 587.725:1.83e-010) ( 269.161:7.32e-011)
  2 1608.660 ( 587.725:1.36e-010) ( 269.161:1.65e-011)
  0      1608.66: 0.00170148 0.00371525
  1      1608.66: 0.00170148 0.00371525
  0      11444.3: -1.57468 -0.114374 0.0891461 0.295675 0.322676

-0.0819240 0.0613226 -0.278625 0.252676 0.297048 0.00170148 0.00371525
1 10461.4: -1.57468 -0.114375 0.0891456 0.295675 0.322677
-0.0819245 0.0613221 -0.278625 0.252676 0.297048 0.991395 0.146916
2 10453.7: -1.57501 -0.118004 0.0914816 0.325860 0.316566
-0.101131 0.0995624 -0.273603 0.254018 0.290755 0.987977 0.148760
3 10452.4: -1.57627 -0.106030 0.110693 0.344082 0.324971
-0.0605686 0.106017 -0.267820 0.245485 0.293816 0.976769 0.154694
4 10451.5: -1.57797 -0.0856623 0.117621 0.334970 0.344039
-0.0620508 0.146502 -0.274762 0.257380 0.289187 0.968650 0.161734
5 10450.2: -1.57831 -0.0912595 0.116721 0.344484 0.342080
-0.0541054 0.139780 -0.273456 0.253567 0.291741 0.966484 0.162502
6 10450.1: -1.58093 -0.0960249 0.120939 0.348483 0.333461
-0.0497757 0.138781 -0.271218 0.250089 0.293405 0.960659 0.169695
7 10449.8: -1.58338 -0.0947018 0.111567 0.349242 0.340198
-0.0491439 0.142989 -0.272130 0.253299 0.291556 0.953538 0.175865
8 10449.7: -1.58601 -0.0918766 0.121701 0.342860 0.342149
-0.0469333 0.143516 -0.272566 0.251350 0.294516 0.946432 0.181555
9 10449.6: -1.58943 -0.0910486 0.119831 0.352018 0.337230
-0.0454451 0.140744 -0.272584 0.256178 0.290521 0.939746 0.188275
10 10449.5: -1.59166 -0.0935204 0.116089 0.350666 0.341477
-0.0510304 0.145357 -0.270167 0.247932 0.296975 0.933589 0.191757
11 10449.4: -1.59447 -0.0957850 0.120865 0.343099 0.343630
-0.0473610 0.143548 -0.269864 0.255472 0.290163 0.927840 0.195228
12 10449.1: -1.59658 -0.0901759 0.115450 0.350433 0.337106
-0.0458197 0.142501 -0.272300 0.252706 0.296086 0.921275 0.197706
13 10449.0: -1.60106 -0.0990970 0.119617 0.350897 0.341253
-0.0521281 0.143267 -0.269335 0.253346 0.294103 0.914170 0.202652
14 10448.9: -1.60360 -0.0884343 0.118272 0.344260 0.339332
-0.0487273 0.139916 -0.268830 0.255000 0.292972 0.906302 0.204724
15 10448.8: -1.60708 -0.0952676 0.116544 0.350083 0.341797
-0.0438318 0.142868 -0.273987 0.255999 0.298785 0.898871 0.208172
16 10448.6: -1.61004 -0.0936384 0.119330 0.347368 0.338683
-0.0502022 0.147287 -0.265043 0.253930 0.293356 0.891785 0.209803
17 10448.4: -1.61572 -0.0922092 0.119692 0.348542 0.342165
-0.0453877 0.138443 -0.265999 0.256307 0.294703 0.883089 0.215247
18 10448.4: -1.61897 -0.0915042 0.119826 0.346438 0.340360
-0.0538914 0.143168 -0.273599 0.260039 0.300747 0.876663 0.215492
19 10448.1: -1.62170 -0.0959069 0.114654 0.350710 0.339778
-0.0497085 0.142583 -0.264006 0.254848 0.298294 0.869750 0.215881
20 10448.0: -1.62425 -0.0925439 0.121244 0.342900 0.337405
-0.0463290 0.142340 -0.266442 0.261394 0.295969 0.861491 0.216977
21 10447.8: -1.63033 -0.0931746 0.119288 0.346826 0.344990
-0.0511664 0.144844 -0.264393 0.258442 0.302008 0.853196 0.217943
22 10447.7: -1.63145 -0.0916493 0.118219 0.352653 0.337064
-0.0455886 0.138990 -0.264261 0.263362 0.297954 0.845762 0.217530
23 10447.4: -1.63584 -0.0963003 0.117473 0.344293 0.334583
-0.0471378 0.145940 -0.261730 0.260632 0.302341 0.838119 0.219307
24 10447.3: -1.63779 -0.0939463 0.112834 0.349643 0.342489
-0.0464460 0.141193 -0.262403 0.264623 0.301302 0.828109 0.218743
25 10447.1: -1.64064 -0.0902682 0.123597 0.349856 0.343063
-0.0531242 0.139255 -0.260173 0.263578 0.303512 0.820044 0.219590
26 10446.8: -1.64322 -0.0935995 0.115354 0.350843 0.338844
-0.0474707 0.141749 -0.260037 0.264904 0.305199 0.809290 0.219342
27 10446.6: -1.64619 -0.0945572 0.119069 0.342510 0.338353
-0.0456821 0.147251 -0.257505 0.267071 0.304463 0.798134 0.219737
28 10446.3: -1.64999 -0.0947331 0.118412 0.349323 0.341641
-0.0476797 0.140415 -0.256079 0.268139 0.307440 0.786893 0.221035
29 10446.2: -1.65084 -0.0886278 0.118513 0.347099 0.337841
-0.0542178 0.146136 -0.256303 0.268253 0.309310 0.775711 0.219820
30 10445.8: -1.65368 -0.0922684 0.119903 0.347534 0.339643
-0.0467803 0.141972 -0.253972 0.271075 0.309212 0.763495 0.220808
31 10445.7: -1.65432 -0.0934434 0.114649 0.351249 0.341609
-0.0511498 0.147058 -0.254179 0.267805 0.313519 0.751625 0.219946
32 10445.3: -1.65655 -0.0926586 0.119584 0.348001 0.339997
-0.0492817 0.143213 -0.252695 0.272859 0.310855 0.738776 0.221235
33 10445.1: -1.65724 -0.0930273 0.115031 0.351075 0.341181
-0.0465371 0.141509 -0.252119 0.268540 0.315546 0.725421 0.220247
34 10444.7: -1.65927 -0.0927543 0.118641 0.348636 0.340453
-0.0497414 0.144647 -0.251144 0.273531 0.312746 0.711868 0.221569
35 10444.4: -1.66014 -0.0927254 0.117734 0.349532 0.340062
-0.0444686 0.139415 -0.250910 0.272214 0.315254 0.697846 0.220846
36 10441.9: -1.69136 -0.104869 0.114555 0.361175 0.357164
-0.0599348 0.140898 -0.232009 0.280566 0.334682 0.511023 0.248880
37 10436.0: -1.70375 -0.0828958 0.116911 0.349359 0.350304
-0.0512119 0.156769 -0.216600 0.296166 0.352977 0.320550 0.255465
38 10434.6: -1.70384 -0.0880833 0.121505 0.352662 0.345165
-0.0429543 0.146445 -0.218435 0.306303 0.345228 0.316458 0.254844
39 10434.2: -1.70422 -0.0934200 0.122745 0.347648 0.341108
-0.0496339 0.146789 -0.218789 0.304552 0.349584 0.299201 0.252209
40 10433.7: -1.70444 -0.0925859 0.115720 0.350862 0.340392
-0.0469562 0.141048 -0.216638 0.310348 0.347099 0.282092 0.249917
41 10433.3: -1.70446 -0.0931099 0.118574 0.346919 0.339547
-0.0516847 0.143506 -0.213742 0.309185 0.352231 0.263546 0.246707
42 10432.6: -1.70471 -0.0941059 0.113513 0.351775 0.338769
-0.0495017 0.139931 -0.208146 0.319561 0.356341 0.225173 0.237935
43 10432.4: -1.70797 -0.0937163 0.121158 0.343195 0.343718
-0.0530556 0.140490 -0.193316 0.328469 0.374068 0.205060 0.213949
44 10432.2: -1.71930 -0.0944377 0.117711 0.350098 0.336539
-0.0507862 0.141410 -0.175205 0.348005 0.387963 0.197098 0.190250
45 10432.1: -1.72151 -0.0949748 0.116203 0.344533 0.342755
-0.0494401 0.137980 -0.173972 0.351927 0.392206 0.197160 0.187444
46 10432.1: -1.72269 -0.0948574 0.117125 0.346960 0.339561
-0.0515517 0.139812 -0.171871 0.353255 0.393072 0.196681 0.187603
47 10432.1: -1.72279 -0.0949262 0.117043 0.347170 0.339564
-0.0509965 0.139315 -0.171544 0.353063 0.393329 0.196471 0.187595
48 10432.1: -1.72306 -0.0947929 0.117129 0.347058 0.339491
-0.0511342 0.139607 -0.171074 0.353431 0.393525 0.195959 0.187574
49 10432.1: -1.72379 -0.0949714 0.116977 0.347264 0.339587
-0.0507304 0.139303 -0.170283 0.354277 0.394605 0.195653 0.187622
50 10432.1: -1.73745 -0.0949212 0.117176 0.346877 0.338784
-0.0514425 0.139079 -0.154894 0.371388 0.410965 0.196248 0.187693
51 10432.0: -1.74347 -0.0950768 0.116443 0.347248 0.340567
-0.0494151 0.141337 -0.145484 0.376406 0.418066 0.196017 0.187831
52 10432.0: -1.74954 -0.0940385 0.118101 0.347600 0.340126
-0.0478509 0.143164 -0.139359 0.385729 0.424524 0.196150 0.187119
53 10432.0: -1.75110 -0.0936333 0.117473 0.347457 0.340236
-0.0495394 0.140504 -0.138277 0.385992 0.426828 0.195005 0.188405
54 10432.0: -1.75362 -0.0954679 0.116741 0.346808 0.339022
-0.0500229 0.140646 -0.136244 0.388144 0.427714 0.194715 0.189040
55 10432.0: -1.75554 -0.0949921 0.117023 0.347058 0.339582
-0.0496439 0.141035 -0.134474 0.389739 0.430382 0.194467 0.186809
56 10432.0: -1.75591 -0.0944204 0.117272 0.347378 0.339771
-0.0498677 0.140480 -0.133556 0.391030 0.430849 0.194460 0.186355
57 10432.0: -1.75622 -0.0945095 0.117389 0.347319 0.339824
-0.0499044 0.140630 -0.132562 0.391734 0.432105 0.194408 0.187217
58 10432.0: -1.75686 -0.0947003 0.117059 0.347200 0.339619
-0.0495625 0.140879 -0.131663 0.392896 0.432997 0.194223 0.187654
59 10432.0: -1.75778 -0.0947472 0.117253 0.347206 0.339628
-0.0495707 0.140869 -0.130626 0.393636 0.433921 0.194453 0.186924
60 10432.0: -1.75877 -0.0944993 0.117209 0.347352 0.339856
-0.0498309 0.140826 -0.129775 0.394661 0.434882 0.194274 0.186688
61 10432.0: -1.75948 -0.0944810 0.117426 0.347291 0.339689
-0.0496809 0.140634 -0.128936 0.395592 0.435697 0.194265 0.187723
62 10432.0: -1.75997 -0.0947607 0.117194 0.347261 0.339698
-0.0495161 0.140802 -0.127874 0.396307 0.436611 0.194448 0.186709
63 10432.0: -1.75997 -0.0946737 0.117224 0.347231 0.339640
-0.0496096 0.140894 -0.127978 0.396412 0.436636 0.194408 0.186713
64 10432.0: -1.76005 -0.0946805 0.117222 0.347294 0.339677
-0.0495418 0.140844 -0.127949 0.396448 0.436763 0.194315 0.186808
65 10432.0: -1.76015 -0.0946524 0.117252 0.347272 0.339682
-0.0495778 0.140898 -0.127841 0.396564 0.436825 0.194276 0.186895
66 10432.0: -1.76026 -0.0946463 0.117233 0.347280 0.339677
-0.0495408 0.140861 -0.127736 0.396679 0.436936 0.194229 0.186908
67 10432.0: -1.76037 -0.0946545 0.117245 0.347265 0.339681
-0.0495587 0.140902 -0.127618 0.396777 0.437052 0.194202 0.186926
68 10432.0: -1.76046 -0.0946495 0.117251 0.347297 0.339682
-0.0495406 0.140898 -0.127506 0.396928 0.437150 0.194192 0.186917
69 10432.0: -1.76055 -0.0946422 0.117237 0.347264 0.339676
-0.0495445 0.140893 -0.127380 0.397023 0.437290 0.194186 0.186930
70 10432.0: -1.76066 -0.0946661 0.117261 0.347292 0.339685
-0.0495541 0.140922 -0.127271 0.397146 0.437395 0.194167 0.186931
71 10432.0: -1.76090 -0.0946560 0.117228 0.347271 0.339666
-0.0495355 0.140895 -0.127036 0.397390 0.437615 0.194173 0.186938
72 10432.0: -1.76094 -0.0946313 0.117272 0.347291 0.339721
-0.0495014 0.140922 -0.126762 0.397597 0.437908 0.194168 0.187017
73 10432.0: -1.76117 -0.0946427 0.117274 0.347272 0.339696
-0.0495377 0.140953 -0.126576 0.397825 0.438082 0.194202 0.186803
74 10432.0: -1.76158 -0.0946616 0.117253 0.347316 0.339677
-0.0495179 0.140918 -0.126503 0.397935 0.438176 0.194094 0.186901
75 10432.0: -1.76140 -0.0946345 0.117251 0.347299 0.339693
-0.0495395 0.140916 -0.126245 0.398162 0.438420 0.194118 0.186986
76 10432.0: -1.76141 -0.0946363 0.117267 0.347278 0.339688
-0.0495374 0.140918 -0.126244 0.398163 0.438431 0.194115 0.186983
77 10432.0: -1.76143 -0.0946396 0.117255 0.347286 0.339689
-0.0495327 0.140920 -0.126237 0.398173 0.438435 0.194114 0.186975
78 10432.0: -1.76147 -0.0946394 0.117259 0.347277 0.339683
-0.0495314 0.140928 -0.126219 0.398188 0.438453 0.194112 0.186960
79 10432.0: -1.76169 -0.0946427 0.117253 0.347281 0.339694
-0.0495116 0.140935 -0.126132 0.398263 0.438534 0.194134 0.186893
80 10432.0: -1.76166 -0.0946452 0.117262 0.347287 0.339683
-0.0495108 0.140937 -0.125985 0.398428 0.438681 0.194128 0.186879
81 10432.0: -1.76189 -0.0946304 0.117263 0.347296 0.339691
-0.0495325 0.140936 -0.125929 0.398483 0.438741 0.194137 0.186972
82 10432.0: -1.76190 -0.0946413 0.117247 0.347281 0.339689
-0.0495284 0.140929 -0.125781 0.398617 0.438904 0.194099 0.186915
83 10432.0: -1.76201 -0.0946397 0.117254 0.347278 0.339693
-0.0494968 0.140946 -0.125642 0.398758 0.439026 0.194118 0.186973
84 10432.0: -1.76218 -0.0946350 0.117265 0.347288 0.339688
-0.0495205 0.140928 -0.125534 0.398871 0.439121 0.194086 0.186879
85 10432.0: -1.76226 -0.0946434 0.117254 0.347285 0.339675
-0.0495004 0.140968 -0.125402 0.399021 0.439273 0.194094 0.186884
86 10432.0: -1.76230 -0.0946341 0.117261 0.347287 0.339686
-0.0494978 0.140955 -0.125331 0.399077 0.439348 0.194119 0.186884
87 10432.0: -1.76230 -0.0946341 0.117261 0.347287 0.339686

-0.0494978 0.140955 -0.125331 0.399077 0.439348 0.194119 0.186884
>

-----Original Message-----

From: Douglas Bates [mailto:dmbates@gmail.com] Sent: Friday, January 27, 2006 6:33 PM
To: White, Charles E WRAIR-Wash DC
Subject: Re: lme4_0.995-2/Matrix_0.995-4 upgrade introduces error messages (change management)

Sorry to hear of the difficulties, Charles.

One thing to try is to turn on the verbose output so fit your models after setting

options(verbose=TRUE)

Another thing that may be interesting to try is to go to optimization of the Laplace approximation deviance directly without doing any PQL iterations.

My theory has been that the PQL iterations help to stabilize the optimization process but it appears that sometimes they do more harm than good.

Can you let me know what the verbose output shows? The thing to watch for is what I call "ping-ponging" of the PQL iterations. One set of iterations converges to one optimum that determines weights that send it to another optimum that determines weights that sends it back to the original optimum.

On 1/27/06, White, Charles E WRAIR-Wash DC <charles.edwin.white@us.army.mil> wrote: > I'll address two issues. The first is today's error message and the other is change management for contributed packages on CRAN.

>
> TODAY'S ERROR MESSAGE
>
> I switched from the 0.995-1 versions of lme4 and Matrix to those
referenced in the subject line this afternoon. Prior to using these packages on anything else, I applied them to code that 'worked' (provided numerical results with no error messages) under the previous set of packages. Since I can't provide the data, I realize this post may be of limited usefulness. Rightly or wrongly, I've regressed my R installation back to the 0.995-1 versions of lme4/Matrix... so I don't think that I continue to have a problem.
>
> R version 2.2.1, 2005-12-20, i386-pc-mingw32
>
> attached base packages:
> [1] "methods"   "stats"     "graphics"  "grDevices" "utils"
"datasets"
> [7] "base"
>
> other attached packages:
>      lme4   lattice    Matrix
> "0.995-2" "0.12-11" "0.995-4"
>
> > options(show.signif.stars=FALSE)
> >

m1a<-lmer(cbind(prevented,control.count)~repellant+hour+(1|volunteer)+(1 |date),
> + family=binomial(link='probit'), method='Laplace') > Error in dev.resids(y, mu, weights) : argument wt must be a numeric vector of length 1 or length 219
> > # probit doesn't converge
> >
m1b<-lmer(cbind(prevented,control.count)~repellant+hour+(1|volunteer)+(1 |date),
> + family=binomial, method='Laplace')
> Error in dev.resids(y, mu, weights) : argument wt must be a numeric vector of length 1 or length 219
> > # logit is overdispersed
> >
m1<-lmer(cbind(prevented,control.count)~repellant+hour+(1|volunteer)+(1| date),
> + family=quasibinomial, method='Laplace') > Error in glm.fit(X, Y, weights = weights, offset = offset, family = family, :
>         NAs in V(mu)
> > m2<-lmer(cbind(prevented,control.count)~hour+(1|volunteer)+(1|date),
> + family=quasibinomial, method='Laplace')
> Error in glm.fit(X, Y, weights = weights, offset = offset, family =
family,  :
>         NAs in V(mu)
>
> CHANGE MANAGEMENT

>
> Does CRAN keep old versions of contributed packages someplace? If not, the strategy I've implemented today is to maintain my own repository of contributed packages that I use. Stuff happens and change management is good.
>
> Chuck
>
> Charles E. White, Senior Biostatistician, MS
> Walter Reed Army Institute of Research
> 503 Robert Grant Ave., Room 1w102
> Silver Spring, MD 20910-1557
> 301 319-9781
> Personal/Professional Site:
> http://users.starpower.net/cwhite571/professional/
>
>

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