A cost-benefit analysis of demand for food.

Laboratory studies of consumer demand theory require assumptions regarding the definition of price in the absence of a medium of exchange (money). In this study we test the proposition that the fundamental dimension of price is a cost-benefit ratio expressed as the effort expended per unit of food value consumed. Using rats as subjects, we tested the generality of this "unit price" concept by varying four dimensions of price: fixed-ratio schedule, number of food pellets per fixed-ratio completion, probability of reinforcement, and response lever weight or effort. Two levels of the last three factors were combined in a 2 x 2 x 2 design giving eight groups. Each group was studied under a series of six FR schedules. Using the nominal values of all factors to determine unit price, we found that grams of food consumed plotted as a function of unit price followed a single demand curve. Similarly, total work output (responses x effort) conformed to a single function when plotted in terms of unit price. These observations provided a template for interpreting the effects of biological factors, such as brain lesions or drugs, that might alter the cost-benefit ratio.     

Premature conclusions about the signal-to-noise ratio in structural equation modeling research: A commentary on Yuan and Fang (2023)

In a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller standard errors, and thus corresponds to greater values of the [SNR].” In our commentary, we show that Yuan and Fang have made several incorrect assumptions and claims. Consequently, we recommend that empirical researchers not base their methodological choice regarding CB-SEM and regression analysis with composites on the findings of Yuan and Fang as these findings are premature and require further research.     

传统统计方法面临的挑战:元分析方法

利用计算机构造实验组和控制组总体,进行传统统计方法与元分析比较实验研究。在实验组总体高出控制组总体０．５０个标准差的提下,传统ｔ检验的统计检验能力（Ｐ）仅为为４１％;而利用元分析的方法进行统计分析,其结果与计算机构造模型有很高的一致性从而提出元分析方法在进入心理学实验研究和证实理论方面的有效性和可靠性,以及传统统计方法面临挑战的事实。     

A general linear model for estimating effect size in the presence of publication bias

When the process of publication favors studies with smallp-values, and hence large effect estimates, combined estimates from many studies may be biased. This paper describes a model for estimation of effect size when there is selection based on one-tailedp-values. The model employs the method of maximum likelihood in the context of a mixed (fixed and random) effects general linear model for effect sizes. It offers a test for the presence of publication bias, and corrected estimates of the parameters of the linear model for effect magnitude. The model is illustrated using a well-known data set on the benefits of psychotherapy.Authors' note: The contributions of the authors are considered equal, and the order of authorship was chosen to be reverse-alphabetical.     

Choosing what to choose from: Preference for inclusion over exclusion when constructing consideration sets from large choice sets

Decision making is a two‐stage process, consisting of, first, consideration set construction and then final choice. Decision makers can form a consideration set from a choice set using one of two strategies: including the options they wish to further consider or excluding those they do not wish to further consider. The authors propose that decision makers have a relative preference for an inclusion (vs. exclusion) strategy when choosing from large choice sets and that this preference is driven primarily by a lay belief that inclusion requires less effort than exclusion, particularly in large choice sets. Study 1 demonstrates that decision makers prefer using an inclusion (vs. exclusion) strategy when faced with large choice sets. Study 2 replicates the effect of choice set size on preference for consideration set construction strategy and demonstrates that the belief that exclusion is more effortful mediates the relative preference for inclusion in large choice sets. Studies 3 and 4 further support the importance of perceived effort, demonstrating a greater preference for inclusion in large choice sets when decision makers are primed to think about effort (vs. accuracy; Study 3) and when the choice set is perceived as requiring more effort because of more information being presented about each alternative (vs. more alternatives in the choice set; Study 4). Finally, Study 5 manipulates consideration set construction strategy, showing that using inclusion (vs. exclusion) in large choice sets leads to smaller consideration sets, greater confidence in the decision process, and a higher quality consideration set.     

Looking at remembering: Eye movements,pupil size,and autobiographical memory

To examine the relationship between visual imagery and autobiographical memory, eye position and pupil size were recorded while participants first searched for memories and then reconstructed the retrieved memories (Experiment 1), or only searched for memories (Experiment 2). In Experiment 1, we observed that, although recollective experience was not associated with the number of fixations per minute, memories that took longer to retrieve were linked to increased pupil size. In Experiment 2, we observed that directly retrieved memories were recalled more quickly and were accompanied by smaller pupils than generatively retrieved memories. After correcting for response time, retrieval mode also produced an effect, showing that decreased pupil size is not simply due to directly retrieved memories being recalled more quickly. These findings provide compelling evidence that objective measures, such as pupil size, can be used alongside subjective measures, such as self-reports, to distinguish between directly retrieved and generatively retrieved memories.     

Body size as a determinant of aggression during heterosexual encounters in hormone-treated gonadectomized pigs

Aggressive and sexual behavior was studied in 5-minute paired encounters between testosterone-treated castrated boars and estrogen-treated ovariectomized gilts. The boars were either 15 kg heavier (N = 6), or lighter (N = 6), than the gilts (N = 8). Tests were carried out over a 4-week period, during which time each boar was paired once with each gilt; the procedure was replicated over a further 4 weeks. Gilts usually initiated the aggression, especially in the first 4-week period; however, the degree of aggression was positively correlated with body size, irrespective of sex. Aggression was reduced in the second 4-week period in both sexes in tests with large, but not with small, boars. Large boars were more sexually active than small boars, and their sexual performance improved markedly with time, unlike that of the small boars. Champing was positively correlated with aggression duration in pigs of both sexes, and salivation was seen more often in boars than gilts.     

When is the Wilcoxon–Mann–Whitney procedure a test of location? Implications for effect-size measures

The Wilcoxon–Mann–Whitney procedure is invariant under monotone transformations but its use as a test of location or shift is said not to be so. It tests location only under the shift model, the assumption of parallel cumulative distribution functions (cdfs). We show that infinitely many monotone transformations of the measured variable produce parallel cdfs, so long as the original cdfs intersect nowhere or everywhere. Thus there are infinitely many effect sizes measured as shifts of medians, invalidating the notion that there is one true shift parameter and thereby rendering any single estimate dubious. Measuring effect size using the probability of superiority alleviates this difficulty.     

Misunderstandings and omissions in textbook accounts of effect sizes

There have been frequent attempts in psychology to reduce the reliance on null hypothesis significance testing (NHST) as the criterion for establishing the importance of results. Many authorities now recommend the reporting of effect sizes (ESs) as a supplement or alternative to NHST. However, there is extensive specialist literature highlighting problems associated with the use and interpretation of ESs. A review of the coverage of ESs in over 100 textbooks on statistical analysis in behavioural science revealed widespread neglect of ESs and the relevant critical issues that have widespread coverage in the more specialist literature. For example, many textbooks claim that ESs should be interpreted as a simple measure of the practical real-world importance of a result despite the fact that ESs are profoundly influenced by features of design and analysis strategy. We seek to highlight areas of misunderstanding about ESs found in the pedagogical literature in the light of the more specialist literature and make recommendations to researchers for the appropriate use and interpretation of ESs. This is critical as statistics textbooks have a crucial role in the education of researchers.