简析社会学理论检验中的演绎方法

通过介绍和分析社会学中的演绎逻辑,提出演绎逻辑在社会学理论检验过程中具有假设推演的重要作用,这同它在自然科学中扩充知识的功能不同。社会学中的演绎逻辑具有逻辑演绎和经验演绎两种类型,它们具有各自的优点及不足,因此在社会学理论检验过程中应将两者有机结合,扬长避短。     

论中国回族及其文化

回族是在中国历史上发展形成的一个民族群体,并对中国社会发生重大的影响。把民族与宗教信仰紧密联系在一起,是中国回族最突出的特点,也是最重要的特点。中国回族实际上是直接受到两种思想和两种文化的影响和教育。中国回族先民在融会贯通伊斯兰思想和儒家思想方面,有许多创新和独到之处,积累了丰富的经验,提出了许多切实可行的理论和观点,取得了很好的效果,也树立了不同思想和文化之间交流和对话的典范。今天,在新形势下,我们更应该发扬这种精神,积极创造条件,加强民族团结,促进社会和谐。     

Implementing Monte Carlo tests with p-value buckets

Software packages usually report the results of statistical tests using p-values. Users often interpret these values by comparing them with standard thresholds, for example, 0.1, 1, and 5%, which is sometimes reinforced by a star rating (***, **, and *, respectively). We consider an arbitrary statistical test whose p-value p is not available explicitly, but can be approximated by Monte Carlo samples, for example, by bootstrap or permutation tests. The standard implementation of such tests usually draws a fixed number of samples to approximate p. However, the probability that the exact and the approximated p-value lie on different sides of a threshold (the resampling risk) can be high, particularly for p-values close to a threshold. We present a method to overcome this. We consider a finite set of user-specified intervals that cover [0, 1] and that can be overlapping. We call these p-value buckets. We present algorithms that, with arbitrarily high probability, return a p-value bucket containing p. We prove that for both a bounded resampling risk and a finite runtime, overlapping buckets need to be employed, and that our methods both bound the resampling risk and guarantee a finite runtime for such overlapping buckets. To interpret decisions with overlapping buckets, we propose an extension of the star rating system. We demonstrate that our methods are suitable for use in standard software, including for low p-value thresholds occurring in multiple testing settings, and that they can be computationally more efficient than standard implementations.     

A Rejection Principle for Sequential Tests of Multiple Hypotheses Controlling Familywise Error Rates

We present a unifying approach to multiple testing procedures for sequential (or streaming) data by giving sufficient conditions for a sequential multiple testing procedure to control the familywise error rate (FWER). Together, we call these conditions a ‘rejection principle for sequential tests’, which we then apply to some existing sequential multiple testing procedures to give simplified understanding of their FWER control. Next, the principle is applied to derive two new sequential multiple testing procedures with provable FWER control, one for testing hypotheses in order and another for closed testing. Examples of these new procedures are given by applying them to a chromosome aberration data set and finding the maximum safe dose of a treatment.     

An F-type test for detecting departure from monotonicity in a functional linear model

When studying associations between a functional covariate and scalar response using a functional linear model (FLM), scientific knowledge may indicate possible monotonicity of the unknown parameter curve. In this context, we propose an F-type test of monotonicity, based on a full versus reduced nested model structure, where the reduced model with monotonically constrained parameter curve is nested within an unconstrained FLM. For estimation under the unconstrained FLM, we consider two approaches: penalised least-squares and linear mixed model effects estimation. We use a smooth then monotonise approach to estimate the reduced model, within the null space of monotone parameter curves. A bootstrap procedure is used to simulate the null distribution of the test statistic. We present a simulation study of the power of the proposed test, and illustrate the test using data from a head and neck cancer study.     

Myths of Women and Their Reflection in a Therapy Group

One essential dilemma for modern clinical social work involves the relationship between the processes taking place inside the self and the social, cultural, and political developments affecting a person from the outside. The group-analysis approach focuses on four levels of relationships and communication within the group, among others a primordial level of shared myths, archetypical images, and the collective unconscious as an important component of psychotherapy. This article describes group-analysis therapy with women, analyzing a therapeutic process that used social myths to explore the formative institutionalization processes participants had undergone, thereby expanding themselves, growing, and changing.

An Experiment on the Social Facilitation of Gambling Behavior

Research and theory regarding the social facilitation effect generates the expectation that the presence of other gamblers (or co-actors) in a gaming venue is likely to intensify individual gambling behavior and magnify losses. Fifty male and 66 female participants (116 total) played a computer-simulated electronic gaming machine with a fixed winning sequence, followed by an indefinite losing sequence. Measures of the intensity of gambling behavior included the final payout (a direct measure of losses), average bet-size, number of trials played, and the speed of play. Some participants received false feedback from the computer designed to suggest that other gamers in adjacent rooms were playing and sometimes winning at the same game. Persons who received both sight and sound information, including winning bells and instant messages regarding the wins of other (fake) players, placed more bets and lost more money compared to the other conditions with less information.     

The Impact of a Structured-Argument Approach on Group Problem Formulation*

Despite advances in decision analysis and decision support systems, few formulaic procedures exist for undertaking problem formulation, particularly in group settings. This leaves managers with little procedural support for the important task of carefully structuring problems. In a laboratory experiment of 29 intact student teams, we contrasted two problem formulation methodologies: a structured argument approach (based on application of formal reasoning) and a group process approach (based on private idea generation prior to public sharing and evaluation of ideas). The structured argument approach took more time to use and failed to bring about more information search and equivocality reduction in group discussions. On the positive side, however, the structured argument approach led to a greater combination of both coverage of critical issues and consensus on those issues. Use of the structured argument approach also resulted in higher satisfaction with the problem definition and commitment to implementing results of the group meeting. Overall, the results reveal cost/benefit tradeoffs associated with developing argumentation-based procedures for problem formulation.