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D Hedeker

Publications and source records attributed to D Hedeker.

At least 37 records · Page 2Linked to original sources
PubMed1996

Estimating individual influences of behavioral intentions: an application of random-effects modeling to the theory of reasoned action.

Methods are proposed and described for estimating the degree to which relations among variables vary at the individual level. As an example of the methods, M. Fishbein and I. Ajzen's (1975; I. Ajzen & M. Fishbein, 1980) theory of reasoned action is examined, which posits first that an individual's behavioral intentions are a function of 2 components: the individual's attitudes toward the behavior and the subjective norms as perceived by the individual. A second component of their theory is that individuals may weight these 2 components differently in assessing their behavioral intentions. This article illustrates the use of empirical Bayes methods based on a random-effects regression model to estimate these individual influences, estimating an individual's weighting of both of these components (attitudes toward the behavior and subjective norms) in relation to their behavioral intentions. This method can be used when an individual's behavioral intentions, subjective norms, and attitudes toward the behavior are all repeatedly measured. In this case, the empirical Bayes estimates are derived as a function of the data from the individual, strengthened by the overall sample data.

Adolescent↗
PubMed1996

Oropharyngeal regulation of water balance in polydipsic schizophrenics.

OBJECTIVE: Disordered water balance causes substantial morbidity in a subset of schizophrenics and is the consequence of unexplained defects in the regulation of fluid intake and antidiuretic function. We aimed to determine whether oropharyngeal regulation of water balance is altered in these patients. DESIGN: A 2-hour infusion of 3% saline, followed 35 minute later by an oral water load (10 ml/kg over 3 minutes). PATIENTS: Age and sex-matched polydipsic schizophrenics with (n = 5) and without (n = 8) hyponatraemia; non-polydipsic schizophrenics (n = 6); and normal controls (n = 13). MEASUREMENTS: Plasma osmolality, sodium, AVP, and reported desire for water (expressed in cups), determined prior to, and for 30 minutes following, the water load. RESULTS: Plasma osmolality and sodium were consistently lower in the hyponatraemics (P < 0.01). Significant changes did not occur until 20 and 25 minutes, respectively, after oral water loading, and were similar across the four groups. AVP levels were consistently lower in the two polydipsic groups (P < 0.001), fell within 5 minutes after drinking and then levelled off. Neither the acute fall nor the overall pattern of the responses differed across groups. Subjective desire for water also decreased within 5 minutes of drinking, and also to a similar extent, in the four groups. Subsequent levels remained suppressed in the non-polydipsic groups, but rebounded toward baseline in the two polydipsic groups. Thus the overall patterns differed (P < 0.05). At the end of the study, ad lib intake correlated significantly with reported desire for water (r = 0.51, P < 0.002). CONCLUSIONS: The oropharyngeal regulation of water intake is disrupted in polydipsic schizophrenics with and without hyponatraemia. In contrast, the oropharyngeal regulation of AVP secretion appears preserved in the hyponatraemic subset. Previously observed elevations in plasma AVP in this subset are thus unlikely to be related to defects in oropharyngeal regulation.

Adult↗
PubMed1996

The influence of polydipsia on water excretion in hyponatremic, polydipsic, schizophrenic patients.

To determine whether polydipsia is responsible for the altered water excretion in the subset of polydipsic schizophrenic patients who develop hyponatremia, the regulation of antidiuretic function was assessed in polydipsic schizophrenic patients with hyponatremia (n = 5), polydipsic schizophrenic patients without hyponatremia (n = 5), nonpolydipsic schizophrenic patients (n = 6), and normal controls (n = 8). The severity and duration of polyuria were similar in the two polydipsic groups. After oral water loading, maximal free water clearance was similar across all four groups. Free water clearance diminished, however, at lower plasma osmolalities in the hyponatremic polydipsics (P < 0.02) and at higher plasma osmolalities in the normonatremic polydipsics (P < 0.05) relative to that in the nonpolydipsic schizophrenics and normal subjects. The increase in plasma vasopressin after osmotic stimulation with hypertonic saline was slightly, but significantly (P < 0.02), blunted in both polydipsic groups. Hyponatremia occurs in some polydipsic schizophrenics because the relationship between free water clearance to plasma osmolality/sodium is shifted to the left. Polydipsia per se is not responsible for this still unexplained shift.

Adult↗
PubMed1996

Application of random-effects regression models in relapse research.

This article describes and illustrates use of random-effects regression models (RRM) in relapse research. RRM are useful in longitudinal analysis of relapse data since they allow for the presence of missing data, time-varying or invariant covariates, and subjects measured at different timepoints. Thus, RRM can deal with "unbalanced" longitudinal relapse data, where a sample of subjects are not all measured at each and every timepoint. Also, recent work has extended RRM to handle dichotomous and ordinal outcomes, which are common in relapse research. Two examples are presented from a smoking cessation study to illustrate analysis using RRM. The first illustrates use of a random-effects ordinal logistic regression model, examining longitudinal changes in smoking status, treating status as an ordinal outcome. The second example focuses on changes in motivation scores prior to and following a first relapse to smoking. This latter example illustrates how RRM can be used to examine predictors and consequences of relapse, where relapse can occur at any study timepoint.

Alcoholism↗
PubMed1995

The television, school, and family smoking prevention and cessation project. VIII. Student outcomes and mediating variables.

BACKGROUND: This paper presents the student outcomes of a large-scale, social-influences-based, school and media-based tobacco use prevention and cessation project in Southern California. METHODS: The study provided an experimental comparison of classroom delivery with television delivery and the combination of the two in a 2 x 2 plus 1 design. Schools were randomly assigned to conditions. Control groups included "treatment as usual" and an "attention control" with the same outcome expectancies as the treatment conditions. Students were surveyed twice in grade 7 and once in each of grades 8 and 9. The interventions occurred during grade 7. RESULTS: We observed significant effects on mediating variables such as knowledge and prevalence estimates, and coping effort. The knowledge and prevalence estimates effects decayed partially but remained significant up to a 2-year follow-up. The coping effort effect did not persist at follow-ups. There were significant main effects of both classroom training and TV programming on knowledge and prevalence estimates and significant interactions of classroom and TV programming on knowledge (negative), disapproval of parental smoking, and coping effort. There were no consistent program effects on refusal/self-efficacy, smoking intentions, or behavior. CONCLUSIONS: Previous reports demonstrated successful development and pilot testing of program components and measures and high acceptance of the program by students and parents. The lack of behavioral effects may have been the result of imperfect program implementation or low base rates of intentions and behavior.

Child↗
PubMed1995

Initial severity and differential treatment outcome in the National Institute of Mental Health Treatment of Depression Collaborative Research Program.

Random regression models (RRMs) were used to investigate the role of initial severity in the outcome of 4 treatments (cognitive-behavior therapy [CBT], interpersonal psychotherapy [IPT], imipramine plus clinical management [IMI-CM], and placebo plus clinical management [PLA-CM]) for outpatients with major depressive disorder seen in the National Institute of Mental Health Treatment of Depression Collaborative Research Program. Initial severity of depression and impairment of functioning significantly predicted differential treatment effects. A larger number of differences than previously reported were found among the active treatments for the more severely ill patients; this was due, in large part, to the greater power of the present statistical analyses.

Activities of Daily Living↗
PubMed1995

Role of previous claims and specialty on the effectiveness of risk-management education for office-based physicians.

We analyzed the medical malpractice claims data of 1,903 physicians between 1981 and 1990 to assess the efficacy--a reduced incidence of future claims and decreased payout in the event of a claim--of risk-management education for office-based physicians. Physicians were participants in the Oregon Medical Association's medical liability program and represented all recognized specialties and all geographic areas of the state. Each physician's claim and payout history before and after 4 sequential risk-management education programs was entered into a random-effects probit model that allowed for a longitudinal rather than a cross-sectional analysis. For most physicians, there was increased claim vulnerability following 1 or 2 risk-management education courses but decreased vulnerability after additional courses. Among all physicians, having a previous claim substantially increased the risk for a future claim. Risk for an additional claim doubled (from 7% to 14%) for physicians who had a claim in the previous year. Of all specialists who have had claims, anesthesiologists (reduction in claims incidence from 18.8% to 9.1% and in payout from 14.6% to 5%) and obstetrician-gynecologists (reduction in claims incidence from 23.3% to 15.2% and in payout from 11.6% to 4.2%) benefit most from cumulative risk-management education.

Humans↗
PubMed1994

A follow-up of a media-based, worksite smoking cessation program.

Described an examination of data collected 2 years following the onset of a media-based, worksite smoking cessation intervention. Thirty-eight companies in Chicago were randomly assigned to one of two experimental conditions. In the initial 3-week phase, all participants in both conditions received self-help manuals and were instructed to watch a 20-day televised series designed to accompany the manual. In addition, participants in the group (G) condition received six sessions emphasizing quitting techniques and social support. In the second phase, which continued for 12 months, employees in G participated in monthly peer-led support groups and received incentives, while participants in the nongroup (NG) condition received no further treatment. Twenty-four months after pretest, 30% of employees in G were abstinent compared to only 19.5% in NG. This study is one of the few experimentally controlled worksite smoking cessation interventions to demonstrate significant program differences 2 years following the initial intervention.

Employment↗
PubMed1994

Analysis of clustered data in community psychology: with an example from a worksite smoking cessation project.

Although it is common in community psychology research to have data at both the community, or cluster, and individual level, the analysis of such clustered data often presents difficulties for many researchers. Since the individuals within the cluster cannot be assumed to be independent, the use of many traditional statistical techniques that assumes independence of observations is problematic. Further, there is often interest in assessing the degree of dependence in the data resulting from the clustering of individuals within communities. In this paper, a random-effects regression model is described for analysis of clustered data. Unlike ordinary regression analysis of clustered data, random-effects regression models do not assume that each observation is independent, but do assume data within clusters are dependent to some degree. The degree of this dependency is estimated along with estimates of the usual model parameters, thus adjusting these effects for the dependency resulting from the clustering of the data. Models are described for both continuous and dichotomous outcome variables, and available statistical software for these models is discussed. An analysis of a data set where individuals are clustered within firms is used to illustrate features of random-effects regression analysis, relative to both individual-level analysis which ignores the clustering of the data, and cluster-level analysis which aggregates the individual data.

Cluster Analysis↗
PubMed1994

Application of random-effects probit regression models.

A random-effects probit model is developed for the case in which the outcome of interest is a series of correlated binary responses. These responses can be obtained as the product of a longitudinal response process where an individual is repeatedly classified on a binary outcome variable (e.g., sick or well on occasion t), or in "multilevel" or "clustered" problems in which individuals within groups (e.g., firms, classes, families, or clinics) are considered to share characteristics that produce similar responses. Both examples produce potentially correlated binary responses and modeling these person- or cluster-specific effects is required. The general model permits analysis at both the level of the individual and cluster and at the level at which experimental manipulations are applied (e.g., treatment group). The model provides maximum likelihood estimates for time-varying and time-invariant covariates in the longitudinal case and covariates which vary at the level of the individual and at the cluster level for multilevel problems. A similar number of individuals within clusters or number of measurement occasions within individuals is not required. Empirical Bayesian estimates of person-specific trends or cluster-specific effects are provided. Models are illustrated with data from mental health research.

Cluster Analysis↗
PubMed1994

Random-effects regression models for clustered data with an example from smoking prevention research.

A random-effects regression model is proposed for analysis of clustered data. Unlike ordinary regression analysis of clustered data, random-effects regression models do not assume that each observation is independent but do assume that data within clusters are dependent to some degree. The degree of this dependency is estimated along with estimates of the usual model parameters, thus adjusting these effects for the dependency resulting from the clustering of the data. A maximum marginal likelihood solution is described, and available statistical software for the model is discussed. An analysis of a dataset in which students are clustered within classrooms and schools is used to illustrate features of random-effects regression analysis, relative to both individual-level analysis that ignores the clustering of the data, and classroom-level analysis that aggregates the individual data.

Attitude to Health↗
PubMed1994

A random-effects ordinal regression model for multilevel analysis.

A random-effects ordinal regression model is proposed for analysis of clustered or longitudinal ordinal response data. This model is developed for both the probit and logistic response functions. The threshold concept is used, in which it is assumed that the observed ordered category is determined by the value of a latent unobservable continuous response that follows a linear regression model incorporating random effects. A maximum marginal likelihood (MML) solution is described using Gauss-Hermite quadrature to numerically integrate over the distribution of random effects. An analysis of a dataset where students are clustered or nested within classrooms is used to illustrate features of random-effects analysis of clustered ordinal data, while an analysis of a longitudinal dataset where psychiatric patients are repeatedly rated as to their severity is used to illustrate features of the random-effects approach for longitudinal ordinal data.

Adolescent↗
PubMed1994

Differential influence of parental smoking and friends' smoking on adolescent initiation and escalation of smoking.

Smoking-related behaviors and attitudes of significant others (especially friends and parents) are among the most consistent predictors of adolescent smoking. However, theorists remain divided on whether the behaviors of significant others influence adolescent smoking directly or indirectly, and the relative influence of parental and peer smoking on adolescents' own smoking is still a matter of debate. In addition, little research has examined the role of significant others' behavior on different stages of smoking onset. In particular, not much information is available regarding gender and ethnic differences in social influences on smoking behavior. We use structural equation modeling to address these issues. Different theoretical perspectives from cognitive-affective theories (Ajzen 1985; Ajzen and Fishbein 1980) and social learning theories (Akers et al. 1979; Bandura 1969, 1982, 1986) have been integrated into a structural model of smoking influence. The results show that friends' smoking affects adolescent initiation into smoking both directly and indirectly, whereas parental smoking influences smoking initiation only indirectly. The data also show that friends' and parents' smoking affect smoking escalation only indirectly. In general, friends' smoking has a stronger effect on adolescents' smoking behavior, particularly on initiation. Multiple group comparisons of the structural models predicting smoking initiation among males and females reveal that parental approval of smoking plays a significant mediating role for females, but not for males. Comparisons of Whites, Blacks, Hispanics, and other ethnic groups reveal that there are some significant differences in the pathways of friends' influences among the four groups.

Adolescent↗
PubMed1993

Some conceptual and statistical issues in analysis of longitudinal psychiatric data. Application to the NIMH treatment of Depression Collaborative Research Program dataset.

Longitudinal studies have a prominent role in psychiatric research; however, statistical methods for analyzing these data are rarely commensurate with the effort involved in their acquisition. Frequently the majority of data are discarded and a simple end-point analysis is performed. In other cases, so called repeated-measures analysis of variance procedures are used with little regard to their restrictive and often unrealistic assumptions and the effect of missing data on the statistical properties of their estimates. We explored the unique features of longitudinal psychiatric data from both statistical and conceptual perspectives. We used a family of statistical models termed random regression models that provide a more realistic approach to analysis of longitudinal psychiatric data. Random regression models provide solutions to commonly observed problems of missing data, serial correlation, time-varying covariates, and irregular measurement occasions, and they accommodate systematic person-specific deviations from the average time trend. Properties of these models were compared with traditional approaches at a conceptual level. The approach was then illustrated in a new analysis of the National Institute of Mental Health Treatment of Depression Collaborative Research Program dataset, which investigated two forms of psychotherapy, pharmacotherapy with clinical management, and a placebo with clinical management control. Results indicated that both person-specific effects and serial correlation play major roles in the longitudinal psychiatric response process. Ignoring either of these effects produces misleading estimates of uncertainty that form the basis of statistical tests of hypotheses.

Analysis of Variance↗
PubMed1993

Behavioral economics and drug choice: effects of unit price on cocaine self-administration by monkeys.

The application of microeconomic theory to the experimental analysis of behavior has been termed behavioral economics. There has been an increasing interest in applying the concepts of behavioral economics to the study of drug self-administration. In a previously published experiment (Nader and Woolverton, 1992), rhesus monkeys (N = 3) were trained in a discrete-trials choice procedure and allowed to choose between intravenous injections of cocaine (0.03-1.0 mg/kg/injection) and food presentation (1 or 4 pellets; 1 g/pellet) during daily 7-h experimental sessions. When cocaine or food was available under a fixed-ratio (FR) 30 schedule, cocaine intake increased in a dose-related manner for all monkeys. When the response requirement (FR) for cocaine was differentially increased by doubling or quadrupling, the frequency of cocaine choice decreased, shifting the cocaine dose-response function to the right. The present paper is a reanalysis of data from that experiment. Several mathematical models, differentially incorporating the effects of FR, dose and number of food pellets, were compared. When cocaine consumption was analyzed using a multiple linear regression analysis with FR, dose and number of pellets as separate main effects (model I), the R2 was 0.82. When FR and dose were combined into one factor, unit price (UP, responses/mg/kg), and cocaine consumption was analyzed as a linear function of UP (model IIA), the R2 was 0.54. When cocaine consumption was analyzed as a curvilinear, negatively accelerated function of UP (model IIB), the R2 was 0.53. The difference between models I and IIA was statistically significant while models IIA and IIB were not different.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1993

Effects of social support and relapse prevention training as adjuncts to a televised smoking-cessation intervention.

Smokers registering for a televised cessation program who also expressed interest in joining a support group and who had a nonsmoking buddy were randomly assigned to 3 conditions: no-contact control, discussion, and social support. All Ss received a self-help manual and were encouraged to watch the daily TV program. Ss in the discussion and social support conditions were scheduled to attend 3 group meetings (one with a buddy). Social support Ss and buddies received training in support and relapse prevention. A 4th analysis group was composed of Ss who failed to attend any of the scheduled meetings (no shows). There were strong group effects at the end of treatment. Abstinence rates were highest in the social support group, followed, in order, by the discussion group, no shows, and no-contact controls. The social support group improved outcome by increasing both the level of support and program material use (reading the manual and watching TV).

Adult↗