Integration and alternatives: Some current issues in psychoanalytic theory

The first great bridge between psychoanalysis and social work came with the concepts of ego psychology which provided a synthesis between the worlds of the social order and the psychological depths. Current psychoanalytic theorists now question whether any one psychological theory is sufficient to describe the complexity of human experience, and suggest that each theory has a piece of the truth because it states something that is correct about the patient at a particular time in the treatment. Adherence to multiple theories makes a complex problem for the clinical practitioner, who must decide from which perspective to respond to the clinical material of the moment. Psychoanalytic theorists are also questioning the degree to which it is actually the content of the therapist's interpretations which brings about change in the patient. This article suggests that these developments in psychoanalysis, with their emphasis on therapeutic flexibility and the importance of the relationship will renew and reinvigorate the bridge between psychoanalysis and clinical social work.An earlier version of this paper was presented at the First Clinical Conference of the National Federation of Societies for Clinical Social work.     

Vector autoregression and causality: a theoretical overview and simulation study

This paper provides a theoretical overview of Wald tests for Granger causality in levels vector autoregressions (VAR's) and Johansen-type error correction models (ECM's). The theory is based on results in Toda and Phillips (1991a) and allows for stochastic and deterministic trends as well as arbitrary degrees of cointegration. We recommend some operational procedures for conducting Granger causality tests that are based on the Gaussian maximum likelihood estimation of ECM's. These procedures are applicable in the important practical case of testing the causal effects of one variable on another group of variables and vice versa. This paper also investigates the sampling properties of these testing procedures through simulation exercises. Three sequential causality tests in ECM's are compared with conventional causality tests in levels and differences VAR's.     

Acclimation Effects and Separate Opinion Writing in the U.S. Courts of Appeals*

Objective. This article investigates the existence of a freshman effect on separate opinion authorship on the U.S. Courts of Appeals. First, we evaluate the extent to which freshman judges demonstrate unique behavior with respect to writing concurring and dissenting opinions. Second, we examine the potential for background factors to condition any freshman effect. Methods. Individual judges' decisions to author separate opinions, drawn from the Courts of Appeals Database (1960 to 1988), are modeled as a function of a host of individual‐ and circuit‐level factors, including the freshman status of the judge. Results. After controlling for alternative explanations, we find that freshman judges on the courts of appeals are less likely to author concurring and dissenting opinions. Prior federal or appellate court experience, however, does not appear to condition the freshman effect. Conclusion. Freshman circuit court judges experience significant acclimation effects following their elevation to the federal appellate bench.     

A bayesian analysis of trend determination in economic time series

In this paper we provide a comprehensive Bayesian posterior analysis of trend determination in general autoregressive models. Multiple lag autoregressive models with fitted drifts and time trends as well as models that allow for certain types of structural change in the deterministic components are considered. We utilize a modified information matrix-based prior that accommodates stochastic nonstationarity, takes into account the interactions between long-run and short-run dynamics and controls the degree of stochastic nonstationarity permitted. We derive analytic posterior densities for all of the trend determining parameters via the Laplace approximation to multivariate integrals. We also address the sampling properties of our posteriors under alternative data generating processes by simulation methods. We apply our Bayesian techniques to the Nelson-Plosser macroeconomic data and various stock price and dividend data. Contrary to DeJong and Whiteman (1989a,b,c), we do not find that the data overwhelmingly favor the existence of deterministic trends over stochastic trends. In addition, we find evidence supporting Perron's (1989) view that some of the Nelson and Plosser data are best construed as trend stationary with a change in the trend function occurring at 1929.     

Influencing Client Expectations About Career Counseling Using a Videotaped Intervention

Realistic client expectations about career counseling are essential to positive client outcomes. The authors investigated a videotaped intervention designed to influence participants' expectations about career counseling using a pretest/posttest experimental design. As measured by the Expectations About Counseling‐Brief Form (H. E. A. Tinsley, 1982), undergraduate participants who watched the videotaped intervention significantly increased their expectations of personal commitment to career counseling and decreased their expectations of counselor expertise compared with participants who watched a control videotape. A secondary hypothesis, that changes in expectations would positively affect attitudes toward career counseling as measured by the Attitudes Toward Career Counseling Scale (A. R. Rochlen, J. J. Mohr, & B. K. Hargrove, 1999), was not supported.     

Dynamic image analysis using Bayesian shape and texture models

In this paper, we discuss the implementation of fully Bayesian analysis of dynamic image sequences in the context of stochastic deformable templates for shape modelling, Markov/Gibbs random fields for modelling textures, and dynomation.

Throughout, Markov chain Monte Carlo algorithms are used to perform the Bayesian calculations.