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At least 19 recordsLinked to original sources
PubMed1994

The subtyping of schizophrenia in men and women: a latent class analysis.

Latent class analysis on an epidemiologically based series of 447 first contact patients with a broad diagnosis of schizophrenia revealed evidence for two subtypes: a 'neurodevelopmental' type characterized by early onset, poor pre-morbid social adjustment, restricted affect and a male:female ratio of 7:3; and a 'paranoid' type characterized by later onset, persecutory delusions and an almost equal sex ratio. A third 'schizoaffective' subtype, whose existence was less clear cut, was almost entirely confined to females and characterized by dysphoria and persecutory delusions, and had negligible familial risk of schizophrenia. The aetiological, biological and clinical significance of this typology remains to be tested.

Adolescent↗
PubMedDate not supplied

Latent class analysis in chronic disease epidemiology.

Latent class analysis provides a useful framework for the analysis of epidemiological data which may have been mismeasured. In this paper, the latent class model is described in the context of logistic regression with categorical variables, and some examples of its application are provided. In particular, it is shown that adjustment for a misclassified confounding variable can be greatly improved by using the methods presented.

Chronic Disease↗
PubMedDate not supplied

A classification of Scottish infants using latent class analysis.

This paper illustrates the use of latent class analysis to classify 50,000 infants into a small number of classes or case types, as a preliminary to a study of the allocation of neonatal hospital resources throughout Scotland. Information, extracted from a detailed neonatal discharge record, was summarized by 11 clinical and diagnostic catagorical variables. Statistical models incorporating 1 to 6 latent classes were then estimated using the EM algorithm. The 4 class model was chosen because it provided a good description of the data and the resulting classes had a medical interpretation. The factors influencing the choice of model are discussed and goodness of fit tests are presented. The stability of the classes was also investigated using random halves of the data and an earlier comparable data set.

Classification↗
PubMed1990

Latent class analysis of diagnostic agreement.

We describe methods based on latent class analysis for analysis and interpretation of agreement on dichotomous diagnostic ratings. This approach formulates agreement in terms of parameters directly related to diagnostic accuracy and leads to many practical applications, such as estimation of the accuracy of individual ratings and the extent to which accuracy may improve with multiple opinions. We describe refinements in the estimation of parameters for varying panel designs, and apply latent class methods successfully to examples of medical agreement data that include data previously found to be poorly fitted by two-class models. Latent class techniques provide a powerful and flexible set of tools to analyse diagnostic agreement and one should consider them routinely in the analysis of such data.

Algorithms↗
PubMed1994

Latent class analysis of substance abuse patterns.

This chapter discusses use of latent class analysis (LCA) as a tool for identifying substance use patterns in cross-sectional data. LCA serves as an exploratory and data reduction tool that helps clarify the nature of substance use and may provide insight concerning effective prevention strategies. LCA is well suited to categorical data such as typically are collected in substance use research. Use of LCA can be divided into three steps: (1) model comparison and selection, (2) assignment of cases to latent classes, and (3) interpretation of the latent classes. Quantitative indices of model fit may assist model comparison and selection. Latent classes can be interpreted by examining probabilities of substance use in each latent class and by examining differences on exogenous variables. Limitations, extensions, and software for LCA are discussed. An example illustrates use of LCA with actual data collected from a current substance abuse prevention study.

Analysis of Variance↗
PubMed1996

Can we subtype alcoholism? A latent class analysis of data from relatives of alcoholics in a multicenter family study of alcoholism.

We attempt to identify distinctive subtypes of alcoholics using latent class analysis with data from 2551 relatives of alcoholic probands, all participants in the Collaborative Study of the Genetics of Alcoholism. Latent class analysis is a multivariate technique using cross-classified data to identify unobserved ("latent") classes that explain the relationships among observed variables. Data on 37 life-time symptoms of alcohol dependence from 1360 female and 1191 male relatives were analyzed, with a 4 class solution selected as the best fitting among the 2 through 6 class solutions that were examined. We observed the following classes: class 1, nonproblem drinkers (39.6% male, 50% female); class 2, mild alcoholics (persistent desire to stop, tolerance, and blackouts) (31.8% male, 28.7% female); class 3, moderate alcoholics (social, health, and emotional problems) (18.9% male, 14.6% female); and class 4, severely affected alcoholics (withdrawal, inability to stop drinking, craving, health, and emotional problems) (9.7% male, 6.7% female). There was little evidence for the construct of alcohol abuse; endorsement probabilities for abuse symptoms (e.g., arrest and DWIs) were very low for all classes, whereas hazardous use was common among men in class 1. In addition to those in class 3 and class 4, a majority of men in class 2 qualified for DSM-III-R alcohol dependence, suggesting a biomodal distribution of drinkers and alcoholics, with little nondependent problem drinking among men in this high-risk sample. We conclude that, in this sample, alcoholism is not differentiated by symptom profiles but rather lies on a continuum of severity, with the possible exception of withdrawal, which characterized only class 4 individuals.

Adolescent↗
PubMed1990

Latent class analysis of deluded patients.

The internal and external construct validity of 4 severe prognostic psychopathological items is studied in deluded patients. A two-class model of latent structure analysis fits fairly well. One latent class seems to reflect a schizophrenic spectrum while the other class does not include characteristics which are known from one single nosologic entity. Thought disorder is most predictive for schizophrenic class membership, while blunted affect has the least predictive value. This 'schizophrenic' latent class has a fairly high and similar sensitivity to various definitions of schizophrenic disorder. The frequency of the types of delusions differs between the classes.

Affective Symptoms↗
PubMed1998

The structure of psychosis: latent class analysis of probands from the Roscommon Family Study.

BACKGROUND: The nosologic structure of psychotic illness, still influenced as much by historical as empirical perspectives, remains controversial. METHODS: Latent class analysis was applied to detailed symptomatic and outcome assessments of probands (n=343) with broadly defined schizophrenia and affective illness ascertained from a population-based psychiatric registry in Roscommon County, Ireland. First-degree relatives (n=942) were assessed by personal interview and/or review of hospital record. RESULTS: Six classes were found, all of which bore substantial resemblance to current or historical nosologic constructs. In order of decreasing frequency, they were (1) classic schizophrenia, (2) major depression, (3) schizophreniform disorder, (4) bipolar-schizomania, (5) schizodepression, and (6) hebephrenia. These classes differed on many historical and clinical variables not used in the latent class analysis. Compared with relatives of controls, significantly increased rates of major depression were seen in relatives of depressed and schizodepressed probands. Significantly increased rates of bipolar illness were restricted to relatives of bipolar-schizomanic probands. The risks for schizophrenia and schizophrenia spectrum disorders were significantly increased in relatives of all proband classes except major depression. This increase was moderate for bipolar-schizomanic probands, substantial for schizophrenic, schizophreniform, and schizodepressed probands, and marked for hebephrenic probands. CONCLUSIONS: These results suggest a relatively complex typology of psychotic syndromes consistent neither with a unitary model nor with a Kraepelinian dichotomy. The familial vulnerability to psychosis extends across several syndromes, being most pronounced in those with schizophrenialike symptoms. The familial vulnerability to depressive and manic affective illness is somewhat more specific.

Adolescent↗
PubMed1996

Latent class analysis in medical research.

In the introduction we give a brief characterization of the usual measures for indicating the quality of diagnostic procedures (sensitivity, specificity and predictive value) and we refer to their relationship to parameters of the latent class model. Different variants of latent class analysis (LCA) for dichotomous data are described in the following: the basic (unconstrained) model, models with parameters fixed to given values and with equality constraints on parameters, multigroup LCA including mixed-group validation, and linear logistic LCA including its relationship to the Rasch model and to the measurement of change in latent subgroups. The problem with the identifiability of latent class models and the possibilities for statistically testing their fit are outlined. The second part refers to latent class models for polytomous data. Special attention is paid to simple variants having fixed and/or equated parameters and to log-linear extension of LCA with its possibility for including on the latent level. Several examples are presented to illustrate typical applications of the model. The paper ends with some warnings that should be taken into consideration by potential users of LCA.

Clinical Trials as Topic↗
PubMed1989

DSM-III major depressive disorder in the community. A latent class analysis of data from the NIMH epidemiologic catchment area programme.

The fit of the structure of DSM-III major depressive disorder to data from two large epidemiological surveys is assessed by latent class analysis. The surveys were conducted at the Baltimore and Raleigh-Durham sites of the National Institute of Mental Health (NIMH) Epidemiologic Catchment Area Program. Three classes are required to fit the data, and the third class bears a strong resemblance to major depressive disorder, although it requires slightly more symptoms to be present than DSM-III. The derived structure replicates successfully for Baltimore and Raleigh-Durham, with a prevalence of the major depression category of 0.9% for both sites.

Catchment Area, Health↗
PubMed1991

Latent class analysis of organic aspects of obsessive-compulsive disorder in children and adolescents.

Organic aspects of obsessive-compulsive disorder (OCD) have previously been described and hypotheses of biological etiology have been suggested. Sixty-one patients, 8-17 years of age, who fulfilled the DSM-III criteria for OCD in a review of the records were compared with 117 matched control patients for organic features. The indicators chosen for an organic concept were neurological signs, more than mild electroencephalographic abnormality, specific developmental disorder and attention deficit, and their defining property of an organic concept was confirmed by latent class analysis. Neurological signs was the most sensitive and specific indicator. Significantly fewer OCD children than control patients were assigned to the organic class. Almost all the types of obsessive-compulsive symptoms were more related to the non-organic class. Such extroverted symptoms as behavioral problems and loss of temper were significantly more frequent in patients assigned to the latent organic class, whereas symptoms of phobia and depressive mood were more often present in patients belonging to the nonorganic class. No difference was found between OCD patients and controls as to frequency of birth complications. The findings do not support the evidence of OCD having signs of major cerebral disturbance found by conventional neuropediatric methods.

Adjustment Disorders↗
PubMed1992

Observer homogeneity in the histologic diagnosis of Helicobacter pylori. Latent class analysis, kappa coefficient, and repeat frequency.

Four pathologists independently examined 82 antral mucosal biopsy specimens for the presence of Helicobacter pylori and indicated whether their assessments were certain. The pathologists made a positive diagnosis in from 56% to 84% of the specimens (significant heterogeneity, p < 0.01). The frequency of uncertain diagnoses was from 4% to 20% (p < 0.01). Uncertain statements occurred more frequently among negative than among positive diagnoses. For the six pairs of observers the kappa coefficients were between 0.39 and 0.82. By a latent class analysis measures of diagnostic accuracy were calculated comparing the observers' assessments with an estimated consensus diagnosis. The predictive values of a positive diagnosis ranged from 0.70 to 1.00. By calculation of repeat frequencies--that is, the probability that an observer's statement was confirmed by another observer--it became evident that uncertain statements were less frequently (61%) confirmed than were certain ones (85%). It is concluded that observer homogeneity is only moderate with regard to the histologic diagnosis of H. pylori, which should be considered both in daily clinical routine and in scientific studies. Disagreement between observers was associated with negative diagnoses, presumably because the pathologists felt more uncertain in these cases.

Adult↗
PubMedDate not supplied

The value of latent class analysis in medical diagnosis.

Assessment of the value of diagnostic indicators such as symptoms and laboratory tests results from calculation of the sensitivity and specificity of the indicators. Knowledge of the rate of occurrence of the disease allows for additional calculations of the error rates in using an indicator. These calculations are accurate only when the data on which they are based are reliable. If the diagnosis, which is used as the criterion for computing the sensitivity and specificity, is not accurate, then the resulting calculations will be in error. We show how a statistical method, latent class analysis, allows for the estimation of the characteristics of indicators even when an accurate diagnosis is unavailable. In addition, the method deals with several indicators at once, and provides a way to combine the information from all the indicators to make a diagnosis.

Biometry↗
PubMed1996

Random effects models in latent class analysis for evaluating accuracy of diagnostic tests.

When the results of a reference (or gold standard) test are missing or not error-free, the accuracy of diagnostic tests is often assessed through latent class models with two latent classes, representing diseased or nondiseased status. Such models, however, require that conditional on the true disease status, the tests are statistically independent, an assumption often violated in practice. Consequently, the model generally fits the data poorly. In this paper, we develop a general latent class model with random effects to model the conditional dependence among multiple diagnostic tests (or readers). We also develop a graphical method for checking whether or not the conditional dependence is of concern and for identifying the pattern of the correlation. Using the random-effects model and the graphical method, a simple adequate model that is easy to interpret can be obtained. The methods are illustrated with three examples from the biometric literature. The proposed methodology is also applicable when the true disease status is indeed known and conditional dependence could well be present.

AIDS Serodiagnosis↗
PubMed1995

Latent-class analysis of recurrence risks for complex phenotypes with selection and measurement error: a twin and family history study of autism.

The use of the family history method to examine the pattern of recurrence risks for complex disorders such as autism is not straightforward. Problems such as uncertain phenotypic definition, unreliable measurement with increased error rates for more distant relatives, and selection due to reduced fertility all complicate the estimation of risk ratios. Using data from a recent family history study of autism, and a similar study of twins, this paper shows how a latent-class approach can be used to tackle these problems. New findings are presented supporting a multiple-locus model of inheritance, with three loci giving the best fit.

Autistic Disorder↗
PubMedDate not supplied

Using test-retest reliability data to improve estimates of relative risk: an application of latent class analysis.

The paper discusses the problem of interval estimation for the relative risk when some test-retest data are available on random subsamples drawn from case-control studies. It is shown that, although the upper portion of the interval may be very wide indeed, the lower bound of the interval estimate may be improved considerably by the collection of even modest amounts of repeat measurements.

Disease↗
PubMed1995

Patterns of drug use among white institutionalized delinquents in Georgia: evidence from a latent class analysis.

Previous research by Kandel [1] and others indicates that adolescent drug use follows a progression from legal drugs, through marijuana, to hard drugs. In this study of drug use patterns, institutionalized delinquents were found to follow a similar progression of drug use. Unlike previous studies which used "rule of thumb" methods of model assessment, this study uses probabilistic assessment of the models. Importantly, the present study supports a modified gate-way sequence, where cocaine use appears as an intermediate step between marijuana use and use of other hard drugs. It is suggested that widespread availability of cocaine in the late 1980's may have resulted in a new "step" in the drug use sequence.

Adolescent↗