I am trying to determine the number of groups or classes for a latent variable using seven observed variables. I am using Stata 15.1.
I followed example 52g of the Stata manual (Latent profile model), on the section "comparing models", which tells us to look for the smallest AIC and BIC values.
My results produced two low(er) BIC values, in the five class model, and then in the seven class model. This is confusing as I was expecting to obtain a single low value and then go with it. My understanding is that the best solution is five classes. Another source of confusion is that a previous model I estimated using Hierarchical clustering signals the solution is three classes, which is consistent with the literature.
Maybe some of you have insights on this topic? Many thanks.
My code looks as follows:
Code:
gsem (norms trust farming lfunction informal engagement advisory <- ), lclass(C 2) estimates store twoclass gsem (norms trust farming lfunction informal engagement advisory <- ), lclass(C 3) estimates store threeclass gsem (norms trust farming lfunction informal engagement advisory <- ), lclass(C 4) estimates store fourclass gsem (norms trust farming lfunction informal engagement advisory <- ), lclass(C 5) estimates store fiveclass gsem (norms trust farming lfunction informal engagement advisory <- ), lclass(C 6) estimates store sixclass gsem (norms trust farming lfunction informal engagement advisory <- ), lclass(C 7) estimates store sevenclass gsem (norms trust farming lfunction informal engagement advisory <- ), lclass(C 8) estimates store eightclass gsem (norms trust farming lfunction informal engagement advisory <- ), lclass(C 9) estimates store nineclass estimates stats twoclass threeclass fourclass fiveclass sixclass sevenclass eightclass nineclass
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(norms trust farming lfunction informal engagement advisory) . . . . . . . -.98162 -.3114 -.42686 .27697 -.58359 -.9699 -.01755 -1.27795 .07518 -.92345 -.60814 -.41226 -1.04472 -.03326 -.17439 .06842 -.21618 1.90339 .05599 -.46079 .11537 .00181 .34967 1.73676 1.62089 1.70806 .55895 .95268 -1.07155 -.67026 .18111 .09381 -.60163 -.01348 1.24672 -.65683 -.01478 -.42252 .14127 .32071 -.36836 -.41697 -.62188 1.07709 .2193 1.59195 -.77941 .1342 -.82457 . . . . . . . -.19673 -.27395 2.01558 1.58268 1.15111 2.04795 .87557 . . . . . . . . . . . . . . -.23446 -.31216 .38219 -.76928 .67551 .34163 .66063 .66597 .02493 .7812 -.55981 -.53341 .14777 -.02744 .79905 .67628 1.2509 .20092 1.06249 .7914 -.32487 .57796 1.00764 -.01036 -.49744 .72682 .09987 -.28355 -2.1567 -2.00231 -.75437 -.58971 -1.35053 -.96453 -.322 .28847 .48866 1.78863 1.77702 .28262 -.49722 -.70806 2.917 2.1843 1.47226 .17037 1.46298 2.07718 -.79311 -.42906 .01127 -.33037 -.76792 -.3787 1.01925 .38168 -1.28062 -.90478 -.84523 -.70117 -.86212 -.9561 -.07887 -.15234 -.11308 -.42957 -.55775 -1.05749 .16358 -.07475 .01219 .27228 -.82642 -.89828 -.62624 .08204 .52512 -.24257 -.09245 -.19699 .06336 -.42748 -.1867 -.03323 . . . . . . . -.25378 .19178 -.55938 -.83342 -.29252 .0079 1.39661 -.34622 -.23197 -.50193 .01962 -.77826 -.07785 -.54594 -1.33258 -2.12957 -.60777 .1453 -.85057 -.37469 .15513 -.49857 -.32841 .08047 -.85962 .55352 .11355 .83447 . . . . . . . .00208 -.25685 .15314 -.80633 .78764 .58573 -.569 2.44616 1.93312 .43792 .16945 .05415 -.12629 -.81038 -1.16391 -.91032 -1.41753 -.1193 -.59082 -.48461 .4458 . . . . . . . -.63856 -1.29752 -.74769 .63711 -.58303 .14735 1.02066 .80684 1.43026 -.11052 1.79622 -.49766 -.46734 .25756 -.89285 -.2508 -.75942 -.76664 -.94423 -.70646 -.33857 .55308 .30491 .00904 -.71084 .95948 1.22393 .2342 . . . . . . . . . . . . . . .82427 .15126 1.18409 1.81541 .52152 1.28638 -.50343 -1.06096 -.24109 -.44379 -.69832 .67544 -.5215 .93901 .32824 -.22754 -.63507 1.54957 .64834 .78442 .10655 .11212 .36787 .57904 1.75799 -.92055 -.42177 -.80624 -.01378 -.18003 -.18454 -.85153 -.18396 -.31322 -.77143 1.10172 1.12238 .04267 .83061 .18984 .64337 -.48618 .0956 -.64086 -.32717 .65141 -.5537 .44379 -.63879 -.03716 .97456 -.93637 1.40202 .79696 -.2963 .1341 -.11278 .63474 .30942 1.67336 -.72935 -.66114 -.24077 .32976 .95995 .0936 1.41741 .19751 .41717 -.25109 .28598 .94149 -.49551 -.70068 .0374 -.95552 -.62067 -.43843 -.04589 .29333 1.56714 .7755 -.53211 .97443 .90736 .57099 .12578 .68461 .42543 .55269 .03414 1.19604 1.12332 -.48926 -.74625 .88298 -.30151 .43248 . . . . . . . -.58343 .48143 -.38741 -.52045 -.01152 -.45304 -.62327 .57667 .89587 -.80499 -.6647 -.71928 -.12715 -.01692 .03393 -.24292 .03263 .11358 -.42574 .28757 -.38657 -.24131 -.09174 -.2946 -.46846 -.82168 -.35623 .15242 . . . . . . . .1217 .69624 .78358 -.82037 1.5453 .41513 -1.07919 .67261 -.6634 -.66666 -.82749 -.4517 -.182 -.56629 .0297 .76154 -.69922 .98276 .15046 -.87889 -.37813 . . . . . . . 1.14868 -.21988 -.63483 -1.00056 .1877 .75215 .87147 -.00828 .06452 .10774 -.54093 -.26943 -.15246 -.82105 .90453 -.36292 .81872 .08099 1.17278 .42526 .0197 -1.24279 -.8721 -.92597 -.79885 .48879 -.54551 .46449 -.79878 .0201 .08659 .0727 .55572 1.20979 -.15132 .57728 .60675 .25095 .18553 .04941 .37787 .28629 1.16343 1.63819 .81735 .08798 .22632 1.45681 .50109 -.25402 .32468 -.69245 -.77693 -.35289 .28376 -.3427 -.45147 .11576 -.32327 -.68546 .36101 -.15307 -.44881 -.04494 -.06861 .13233 -.90248 .06439 .68085 -.84557 . . . . . . . -.1818 .37248 -.4322 .55371 .64133 .4286 -.27781 1.214 2.02057 1.22313 .09709 -.30147 -.15322 -1.23281 -.30937 .13472 .37401 -.67369 1.07601 -.01124 -.6008 .26423 .02267 -.90632 -.94903 -.59597 .25893 -.1776 . . . . . . . 1.07253 .92323 .88192 1.54814 1.86285 1.49033 -.60765 .23948 .95284 .20922 -.53522 -.98768 -.58779 -.82547 .21964 -.21275 .37773 1.64471 1.00786 .57222 -.71256 -.76473 -.32201 -.40709 1.66059 -.61379 -.23045 .0912 .18023 -.45177 -.81183 -.848 .86402 -.17908 1.68735 -1.49997 -1.19828 -1.28282 -.81151 -.76796 -.6276 .50403 .30224 -.10522 .01976 -.64449 -.02935 .41612 .31947 . . . . . . . -.52266 -1.34936 -.73154 -.76804 -.31962 -.05722 .41141 -.96957 -.78634 .53871 .12362 -.29297 -.09075 .11078 -.78604 -.11771 -.84394 -.80837 -.77715 -.6895 -.24794 .30094 -.48776 -.39064 -.83408 .62239 1.70087 -.06108 -.72275 -.19341 .51569 .30624 -.70441 -.29125 .93915 .20981 -.05193 .47408 -.85325 .38379 .86116 -.68158 -.35538 .03694 -.86964 -.83604 -.72419 -.46129 .42457 -.19418 .13862 .89344 1.42595 1.37781 1.08988 .0639 -.01774 -.21469 -.08852 -.67479 -.96608 .11353 -.91709 . . . . . . . . . . . . . . .58376 1.12999 .99077 .02522 .03026 -.32304 -1.24935 end
Code:
Akaike's information criterion and Bayesian information criterion ----------------------------------------------------------------------------- Model | Obs ll(null) ll(model) df AIC BIC -------------+--------------------------------------------------------------- twoclass | 398 . -2956.341 22 5956.682 6044.384 threeclass | 398 . -2872.062 30 5804.124 5923.718 fourclass | 398 . -2843.916 38 5763.832 5915.317 fiveclass | 398 . -2811.454 46 5714.908 5898.285 sixclass | 398 . -2800.841 54 5709.683 5924.951 sevenclass | 398 . -2737.597 62 5599.194 5846.354 eightclass | 398 . -2724.188 70 5588.376 5867.427 nineclass | 398 . -2712.336 78 5580.671 5891.614 ----------------------------------------------------------------------------- Note: N=Obs used in calculating BIC; see [R] BIC note.
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