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| From | jpitblado@stata.com (Jeff Pitblado, StataCorp LP) |
| To | statalist@hsphsun2.harvard.edu |
| Subject | Re: st: sem |
| Date | Tue, 26 Feb 2013 10:42:12 -0600 |
"Airey, David C" <david.airey@vanderbilt.edu> asks about a recent update to -sem-: > Does anyone find that the recent fix for -sem-: > > -------- update 25feb2013 ----------------- > 1. sem with method(mlmv) will now attempt to fit the specified model > even if the saturated model fails to converge. > > works as advertised? Can someone else confirm on a mac with the > most recent update it works? > > Running my do file below I get the same convergence problem I had > previously. The saturated model is not identified for this model specifiation/data. David can cut down on the number of iterations that -sem- spends trying to fit the saturated model by adding option satopts(iter(10)) With the above mentioned update to -sem-, this option will allow -sem- to quickly continue with the model fit even if the saturated model fails to converge. --Jeff jpitblado@stata.com > clear > > input id read1 read2 read3 read4 age1y age2y age3y age4y > 2 31 47 56 64 7 10 12 14 > 3 36 52 60 75 8 11 13 14 > 13 26 42 53 69 7 9 11 13 > 17 17 37 50 65 6 9 11 13 > 20 27 34 40 47 8 10 12 14 > 21 25 37 41 72 7 9 11 13 > 22 31 49 61 67 8 10 12 14 > 23 32 40 44 59 6 9 11 13 > 26 18 36 46 47 6 8 11 13 > 27 28 28 39 40 8 10 12 14 > 28 21 35 45 51 7 9 11 13 > 29 38 60 60 69 6 9 11 13 > 30 22 40 51 63 7 9 11 13 > 31 72 51 65 76 8 10 12 14 > 32 22 43 60 63 6 9 11 13 > 34 23 49 59 60 7 9 11 13 > 35 19 48 58 74 6 9 11 13 > 36 23 41 57 67 7 9 11 13 > 40 27 41 54 57 8 10 13 14 > 42 18 24 37 54 7 9 12 14 > 44 20 43 50 57 7 9 11 13 > 45 25 43 65 60 7 9 11 13 > 46 16 25 26 37 6 9 11 13 > 47 24 39 44 48 8 10 12 14 > 49 28 50 60 61 6 9 10 12 > 50 36 54 62 77 6 9 11 13 > 51 38 48 54 71 8 10 12 14 > 55 32 36 47 59 8 10 12 14 > 56 26 48 61 74 7 9 11 13 > 57 17 41 54 73 6 8 10 12 > 59 24 37 47 55 8 10 12 14 > 60 23 44 56 72 7 9 11 13 > 62 22 37 48 54 7 9 11 13 > 65 23 45 42 46 7 9 11 14 > 66 23 32 45 53 6 8 11 12 > 67 14 36 52 60 6 9 11 13 > 69 22 33 40 42 7 10 12 14 > 71 18 39 54 58 6 8 11 13 > 72 23 34 45 48 7 9 11 13 > 73 20 29 38 44 7 10 12 13 > 74 19 31 41 51 6 9 11 13 > 76 30 41 50 55 7 9 11 13 > 78 35 42 49 44 8 10 12 14 > 80 18 35 43 54 6 9 11 13 > 81 21 31 39 47 7 10 12 14 > 82 43 53 84 79 7 10 12 14 > 83 21 47 57 52 7 9 11 13 > 84 21 29 45 45 7 9 11 13 > 85 23 38 43 62 6 9 10 12 > 86 18 43 51 72 6 8 11 12 > 87 24 36 46 51 7 10 12 14 > 89 37 50 69 57 8 10 13 14 > 90 20 23 66 58 8 10 12 14 > 91 17 31 54 61 7 9 11 13 > 92 43 56 55 58 7 9 11 13 > 93 18 49 59 70 6 9 11 13 > 95 17 48 58 60 8 10 13 14 > 97 17 37 47 70 6 9 11 13 > 98 47 60 70 80 6 9 11 13 > 101 27 47 59 69 7 9 11 13 > 102 23 42 53 54 7 9 11 13 > 103 18 25 36 47 7 9 11 13 > 106 22 29 34 51 8 10 12 14 > 107 32 36 42 44 7 9 11 13 > 108 22 53 57 61 7 10 12 13 > 109 21 32 49 59 7 9 11 13 > 112 25 40 44 55 6 8 11 13 > 113 18 39 47 58 7 9 11 13 > 115 24 52 58 79 7 10 12 14 > 116 36 38 53 59 6 8 11 12 > 117 16 52 56 66 7 10 12 14 > 118 44 54 58 63 8 10 12 14 > 119 17 40 49 52 7 9 11 13 > 120 40 61 75 66 7 9 11 13 > 121 17 16 22 25 7 9 11 13 > 122 24 50 57 69 7 9 11 13 > 123 21 46 58 68 8 10 12 14 > 124 21 24 34 39 7 10 12 14 > 129 20 40 47 60 7 9 12 14 > 130 18 33 44 61 6 9 11 13 > 134 22 32 46 56 6 9 11 13 > 135 30 47 65 61 7 9 11 13 > 138 24 50 51 58 6 9 11 13 > 139 38 47 63 67 8 10 12 14 > 142 51 57 63 75 8 10 12 14 > 143 32 47 64 74 6 9 11 13 > 144 20 33 40 47 7 9 11 13 > 145 25 39 53 51 7 9 11 13 > 149 18 25 40 41 7 9 11 13 > 150 25 26 37 35 6 9 11 13 > 151 21 34 43 44 7 10 12 14 > 152 17 37 55 63 6 8 10 12 > 153 18 45 56 64 7 9 12 13 > 154 20 23 39 45 6 9 11 13 > 157 35 59 78 71 7 9 11 13 > 158 17 42 48 56 8 10 13 14 > 159 18 33 50 62 8 11 13 14 > 160 17 44 49 58 6 8 11 12 > 161 19 34 35 50 6 9 11 13 > 164 35 50 55 77 7 9 11 13 > 166 18 36 43 51 8 10 12 14 > 171 21 30 37 48 7 9 11 13 > 173 18 25 29 35 7 9 11 13 > 174 21 25 40 33 8 10 13 14 > 175 25 47 53 55 7 9 11 13 > 176 29 45 48 64 7 9 11 13 > 177 19 55 55 55 6 9 11 12 > 178 21 25 31 34 8 10 12 14 > 179 20 36 35 51 7 9 12 13 > 180 28 57 53 58 8 10 12 14 > 182 35 48 59 67 7 10 12 14 > 183 25 51 57 62 6 8 10 12 > 187 18 31 37 43 6 9 11 13 > 188 31 54 66 78 6 8 10 12 > 190 18 24 35 44 6 8 10 12 > 191 22 50 61 81 7 10 12 14 > 195 18 35 45 59 6 8 11 12 > 196 18 39 56 65 8 10 12 14 > 197 23 27 41 44 8 10 13 14 > 199 26 35 41 62 7 10 12 14 > 200 28 38 39 50 7 9 12 13 > 201 30 38 45 55 7 9 11 13 > 202 22 51 60 70 7 10 12 14 > 203 35 43 48 56 8 11 13 14 > 204 18 26 41 40 7 9 11 13 > 207 17 28 39 48 6 9 11 13 > 211 32 50 65 72 7 9 11 13 > 215 16 34 45 57 7 10 12 13 > 217 21 41 49 58 7 10 12 13 > 219 20 36 54 61 6 8 11 12 > 220 35 43 48 59 8 10 12 14 > 221 46 60 61 61 8 10 12 14 > 222 31 52 62 68 7 9 11 13 > 226 19 38 50 48 7 9 11 13 > 227 13 23 25 34 6 9 11 13 > 228 18 32 53 59 8 10 12 14 > 229 23 41 58 69 7 10 12 14 > 231 35 48 58 75 7 10 12 14 > 234 35 48 54 62 8 10 12 14 > 236 32 55 56 49 7 10 12 14 > 240 19 28 33 36 6 9 11 13 > 244 18 35 37 56 6 9 11 13 > 248 31 41 58 74 8 10 12 14 > 250 21 39 50 53 6 9 11 13 > 252 24 36 42 47 7 9 12 13 > 253 19 23 30 28 8 10 12 14 > 255 18 48 65 68 6 9 11 13 > 258 24 38 47 52 7 9 11 13 > 259 33 42 44 66 7 9 11 13 > 262 24 43 55 55 7 10 12 14 > 263 18 38 51 65 6 9 11 13 > 267 33 44 59 58 6 9 11 13 > 269 23 26 31 40 7 9 11 13 > 272 21 41 42 43 8 10 12 14 > 273 15 26 53 56 6 9 11 13 > 275 35 57 61 67 7 9 11 13 > 277 24 54 65 77 7 9 11 13 > 279 12 20 31 34 7 10 11 13 > 280 18 41 53 55 6 9 11 13 > 281 14 22 40 52 6 9 11 13 > 282 27 39 49 55 8 10 12 14 > 287 26 38 58 61 7 9 11 13 > 288 20 39 49 77 6 9 11 13 > 291 37 52 57 78 6 9 11 13 > 295 47 53 61 70 8 10 12 14 > 296 35 57 70 69 8 10 12 14 > 297 26 38 63 61 7 10 12 14 > 299 38 57 62 68 8 10 12 14 > 300 21 30 40 40 7 9 12 13 > 302 18 34 55 64 6 9 11 13 > 303 18 41 50 51 6 8 11 13 > 304 17 32 39 47 7 9 11 13 > 312 20 41 70 80 8 10 12 14 > 313 31 48 48 65 8 10 12 14 > 315 18 49 53 78 7 9 11 13 > 316 26 40 48 51 7 9 11 13 > 318 31 41 47 51 7 10 12 14 > 319 34 46 58 64 8 10 12 14 > 321 28 38 43 50 7 10 12 14 > 322 18 42 51 72 6 8 10 12 > 333 36 56 83 79 7 9 12 13 > 335 19 30 41 44 6 9 11 13 > 337 45 52 61 79 7 9 11 13 > 341 22 47 55 66 7 10 12 14 > 342 22 39 57 60 8 10 12 14 > 344 23 25 29 36 8 10 12 14 > 345 35 40 61 62 6 8 10 12 > 348 26 44 46 50 6 8 11 12 > 350 16 27 40 57 6 9 11 12 > 351 27 49 56 67 7 9 11 13 > 352 18 26 31 40 7 9 11 13 > 353 7 28 37 41 6 8 10 12 > 354 24 32 43 57 8 10 12 14 > 358 18 45 56 58 6 9 11 13 > 359 30 56 51 65 8 10 12 14 > 360 15 38 46 64 6 9 11 13 > 363 35 42 59 63 7 9 11 13 > 368 17 26 31 35 6 9 11 13 > 373 33 49 61 68 8 10 12 14 > 375 22 60 50 56 7 9 12 13 > 378 18 37 44 42 6 9 11 13 > 383 21 55 68 69 7 9 11 13 > 386 40 52 57 80 8 10 12 14 > 388 26 37 46 63 8 10 12 14 > 389 27 40 59 65 7 9 11 13 > 390 20 36 46 55 7 9 11 13 > 392 21 47 70 82 6 9 11 13 > 393 17 21 24 34 8 10 12 14 > 394 28 44 51 60 6 9 11 13 > 395 13 26 34 42 6 9 11 12 > 397 26 25 33 44 6 8 11 12 > 398 56 46 60 63 6 9 11 13 > 399 22 28 34 45 6 9 11 13 > 405 24 39 51 56 7 9 11 13 > end > > *** random intercept, random slope, equal error variances > *** on by wave and by age data; by age has missings as a > *** result of data restructuring > > // works fine > sem (read1 <- Intercept@1 Slope@0 _cons@0) /// > (read2 <- Intercept@1 Slope@1 _cons@0) /// > (read3 <- Intercept@1 Slope@2 _cons@0) /// > (read4 <- Intercept@1 Slope@3 _cons@0), /// > latent(Intercept Slope) /// > cov(Intercept*Slope) /// > var(e.read1@var e.read2@var e.read3@var e.read4@var) /// > means(Intercept Slope) /// > method(ml) > > reshape long read@ age@y, i(id) j(wave) > drop wave > reshape wide read, i(id) j(agey) > > // will not converge > sem (read6 <- Intercept@1 Slope@0 _cons@0) /// > (read7 <- Intercept@1 Slope@1 _cons@0) /// > (read8 <- Intercept@1 Slope@2 _cons@0) /// > (read9 <- Intercept@1 Slope@3 _cons@0) /// > (read10 <- Intercept@1 Slope@4 _cons@0) /// > (read11 <- Intercept@1 Slope@5 _cons@0) /// > (read12 <- Intercept@1 Slope@6 _cons@0) /// > (read13 <- Intercept@1 Slope@7 _cons@0) /// > (read14 <- Intercept@1 Slope@8 _cons@0), /// > latent(Intercept Slope) /// > cov(Intercept*Slope) /// > var(e.read6@var e.read7@var e.read8@var e.read9@var /// > e.read10@var e.read11@var e.read12@var e.read13@var /// > e.read14@var) /// > means(Intercept Slope) /// > method(mlmv) * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/