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The Use of Parameter Restrictions Restricted parameters include those that are xed, in which the value is set to a particular value and not estimated, and those that are constrained to be equal to other parameters in an equivalence set, so that only one parameter is estimated for the entire set In a classic article, Goodman (1974) presented the estimation of restricted latent class models using the EM algorithm Often latent class models are t without the use of any parameter restrictions Such unrestricted models can be quite informative, and are especially useful for exploring new models However, parameter restrictions serve two important roles in latent class models First, parameter restrictions can be used to help in achieving identi cation Both xing and constraining parameters reduces the number of parameters to be estimated, which helps in achieving identi cation.

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Underidenti cation refers to a situation in which there are too many parameters to estimate given the information available in a certain data set One necessary condition for identi cation is that the number of independent parameters to be estimated be less than the number of possible response patterns However, satisfying this condition does not ensure an identi ed model Having a large sample size relative to the number of response patterns helps in identi cation When the sample size is small relative to the number of response patterns (ie, the contingency table is sparse), parameter restrictions can greatly aid in identi cation Second, parameter restrictions are useful tools for specifying or testing various features of a model For example, the parameters de ne the meaning of the latent classes If we have measurement invariance across groups, meaningful comparisons of the latent class probabilities can then be made.

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Structural invariance across groups in the measurement of the latent variable is a testable hypothesis The parameter estimates can be freely estimated in one analysis, and constrained equal across groups in another, and the t of the two models can be compared As an example, a researcher interested in comparing sex differences in the prevalence of two temperament types in a sample of infants may wish to start by comparing a model with all parameters freely estimated to one in which the conditional response patterns are constrained to be equal across the two classes If measurement invariance can be established across classes, this is evidence that the same construct is being measured in males and females, and therefore meaningful cross-sex comparisons of the prevalence of the inhibited and uninhibited types can be made.

and cognition: Readings in cross-cultural psychology (pp 299 309) London: Methuen Reid, P T (1988) Racism and sexism: Comparisons and con icts In P Katz & D Taylor (Eds), Eliminating racism: Pro les in controversy (pp 203 221) New York: Plenum Press Reid, P T (1994) The real problem in the study of culture American Psychologist, 49(6), 524 525 Rogoff, B (1990) Apprenticeship in thinking: Cognitive development in social context New York: Oxford University Press Rogoff, B (1996) Developmental transitions in children s participation in sociocultural activities In M H Arnold Sameroff (Ed), The ve to seven year shift: The age of reason and responsibility (pp 273 294) Chicago: University of Chicago Press Rosaldo, M A (1984) Toward an anthropology of self and feeling In R A Shweder & R A LeVine (Eds), Culture theory : Essays on mind, self, and emotion (pp 137 157).

Another example of a latent class model for which there is a theoretical justi cation to impose parameter restrictions is a hierarchical, or Guttman, model (Rindskopf, 1983)..

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