Community dissatisfaction and depressed mood in Suburbia

Because of contradicting theoretical statements and empirical data, there is a need to specify the exact part that neighborhood and individual characteristics represent in determining mental health related behavior and the livabiiity of residential neighborhoods. This article adds to the understanding of the general problem by exploring the contributions that economic and social status of neighborhoods and individuals make towards depressed mood and community dissatisfaction. The study was limited to men residing in “classic suburbia” in the early 1960s. Seven hypotheses were proposed — the expectancy congruence, the additive, the big reward, and big failure, the atypical person, the reward visibility, and the economic status maintenance hypotheses. Support for the big reward and pan of the additive hypothesis was observed. The relationships presented in the paper clearly demonstrate that to gain an understanding of community dissatisfaction and depressed mood we must examine an individual's social and economic status and that of his neighborhood.     

Weak convergence of bounded influence regression estimates with applications to repeated significance testing

We obtained weak convergence results for bounded influence regression M-estimates and apply the results to sequential clinical trials, with special reference to repeated significance tests in the two-sample problem with covariates.     

Some locally optimal subset selection rules for comparison with a control

Let π₀,π₁,…,π_k be k+1 independent populations. For i=0,1,…,k,π_i has the densit f(x,θ_i), where the (unknown) parameter θ_i belongs to an interval of the real line. Our goal is to select from π₁,… π_k (experimental treatments) those populations, if any, that are better (suitably defined) than π₀ which is the control population. A locally optimal rule is derived in the class of rules for which Pr(π_i is selected)γ_i, i=1,…,k, when θ₀=θ₁=?=θ_k. The criterion used for local optimality amounts to maximizing the efficiency in a certain sense of the rule in picking out the superior populations for specific configurations of θ=(θ₀,…,θ_k) in a neighborhood of an equiparameter configuration. The general result is then applied to the following special cases: (a) normal means comparison — common known variance, (b) normal means comparison — common unknown variance, (c) gamma scale parameters comparison — known (unequal) shape parameters, and (d) comparison of regression slopes. In all these cases, the rule is obtained based on samples of unequal sizes.     

A joined input-output and econometric approach to endogenous calculations of final demands and outputs

The principle of interacting between input-output and econometric systems is illustrated so that both final demands and gross outputs are treated as endogenous. Using a planned economy as an example, a model is constructed with an econometric accelerator and an input-output multiplier. Due to its special structure, the system solution is found with immediate formulas without matrix inverting. Necessary and sufficient conditions for solvability are formulated on the basis of the specific characteristics of the system's matrix. The results are interpreted in terms of familiar economic categories.     

The effect of categorisation on testing for an exponential scale shift

A consequence of the fact that observations of random variables are discrete, is that the usual continuous models are inappropriate. Observations have an induced multinomial distribution where the cell probabilities depend on the form of the unobservable continuous distribution. We discuss one particular case: testing for the scale parameter of an exponential distribution. Sizes, powers and asymptotic relative efficiencies are used to assess the effect of categorisation. There are many parameters and we have not given a complete assessment. However our discussion gives a guide to the approach that may be adopted in similar cases. In the case we discuss, we give a preferred procedure that appears to be more convenient and less objectionable than its obvious competitors.     

Economic psychology

Economic psychology studies the economic behavior of consumers and entrepreneurs. Economic behavior involves decisions on money, time, and efforts. The models of Katona and Strümpel are discussed and a new model is proposed. This new model stresses the cyclical character of economic behavior on a micro and a macro level. Economic psychology is related to organizational psychology, marketing research, mass communication research, economic sociology, and the household production approach. A proposition of the aims and scope of the Journal of Economic Psychology concludes this introductory article.     

Invalidity of average squared error criterion in density estimation

The average squared error has been suggested earlier as an appropriate estimate of the integrated squared error, but an example is given which shows their ratio can tend to infinity. The results of a Monte Carlo study are also presented which suggest the average squared error can seriously underestimate the errors inherent in even the simplest density estimations.     

Sequential and two-stage procedures for selecting the better exponential population covering the case of unknown and unequal scale parameters

The problems of selecting the larger location parameter of two exponential distributions are discussed. When the scale parameters are the same but unknown, we consider the procedure of Desu et al. (1977) in detail, and study some of its exact and asymptotic properties. We indicate how this procedure can be modified along the lines of Mukhopadhyay (1979, 1980) to achieve first-order asymptotic efficiency. We then propose a sequential procedure for this set-up and show that it is asymptotically second-order efficient according to Ghosh and Mukhopadhyay (1981). In case the scale parameters are completely unknown and unequal, we propose a two-stage procedure that guarantees the probability of correct selection to exceed the prescribed nominal level in the preference zone. We do not need any new tables to implement this particular procedure other than those in Krishnaiah and Armitage (1964), Gupta and Sobel (1962), Guttman and Milton (1969). We also propose a sequential method in this case and derive some of its asymptotic properties.     

ESTIMATING THE MAXIMUM (MINIMUM) OF A QUADRATIC FUNCTION UNDER CERTAIN CORRELATION PATTERNS

May nonidentity error correlation patterns encountered in regression theory allow computationally efficient techniques for modifying the usual procedures for constructing confidence intervals and performing F-tests so that valid inferences can be drawn. Such techniques are explored in light of the general theme of this note.     

The Correlated Bivariate Noncentral F Distribution and Its Application

This article proposes the singly and doubly correlated bivariate noncentral F (BNCF) distributions. The probability density function (pdf) and the cumulative distribution function (cdf) of the distributions are derived for arbitrary values of the parameters. The pdf and cdf of the distributions for different arbitrary values of the parameters are computed, and their graphs are plotted by writing and implementing new R codes. An application of the correlated BNCF distribution is illustrated in the computations of the power function of the pre-test test for the multivariate simple regression model (MSRM).