The knowledge content of statistical data

An information-theoretic framework is used to analyze the knowledge content in multivariate cross classified data. Several related measures based directly on the information concept are proposed: the knowledge content (S) of a cross classification, its terseness (Zeta), and the separability (Gamma _X ) of one variable, given all others. Exemplary applications are presented which illustrate the solutions obtained where classical analysis is unsatisfactory, such as optimal grouping, the analysis of very skew tables, or the interpretation of well-known paradoxes. Further, the separability suggests a solution for the classic problem of inductive inference which is independent of sample size.     

Trend in correlated proportions

A random effects probit model is developed for the case in which the same units are sampled repeatedly at each level of an independent variable. Because the observed proportions may be correlated under these conditions, estimating their trend with respect to the independent variable is no longer a standard problem for probit, logit or loglinear analysis. Using a qualitative analogue of a random regressions model, we employ instead marginal maximum likelihood to estimate the average latent trend line. Likelihood ratio tests of the hypothesis of no trend in the average line, and the hypothesis of no differences in average trend lines between experimental treatments, are proposed. We illustrate the model both with simulated data and with observed data from a clinical experiment in which psychiatric patients on two drug therapies are rated on five occasions for the presence or absence of symptoms.Supported by a grant from the MacArthur Foundation and National Science Foundation Grant BNS85-11774.The authors are indebted to James Heckman for calling our attention to the Clark algorithm.     

The Holte Sleeping Technique: An experimental study

The Holte Sleeping Technique is an alternative to medication to facilitate sleep onset in situations of normal stress. The technique is based on a combination of conditioning within the theory of learning, simulation of natural bodily processes, and manipulation of naturally available sleep-releasing stimuli. The author describes the technique and reports on experimental testing of its efficacy. Fifty-six female subjects were selected according to criteria based on questionnaires and sleep logs. The subjects were randomly assigned to a treatment group, a placebo group, and a no-treatment group. A pre-test-post-test design was used. The author questions the generalizability of findings from modern electronic sleep laboratories to the bedrooms of everyday life. In order to optimize the combination of normal stress, objective criteria and generalizability, sleep onset was measured by behavioural criteria based on the "fog-horn procedure" developed by the author. At post-test 67% of the treatment group fell asleep, while only 17% of the placebo group and 25% of the no-treatment group fell asleep. The differences were significant. It is concluded that the Holte Sleeping Technique is highly effective. In a discussion of placebo trials the author argues that traditional medical trials do not take into consideration the differentiating psychological attribution effects occurring by giving the same experimental instruction under different experimental conditions. As a consequence the active treatment is given better conditions than the placebo in traditional clinical trials.     

Measuring concept semantic relatedness through common spatial pattern feature extraction on EEG signals

We study the semantic relationship between pairs of nouns of concrete objects such as “HORSE - SHEEP” and “SWING - MELON” and how this relationship activity is reflected in EEG signals. We collected 18 sets of EEG records; each set containing 150 events of stimulation. In this work we focus on feature extraction algorithms. Particularly, we highlight Common Spatial Pattern (CSP) as a method of feature extraction. Based on these latter, different classifiers were trained in order to associate a set of signals to a previously learned human answer, pertaining to two classes: semantically related, or not semantically related. The results of classification accuracy were evaluated comparing with other four methods of feature extraction, and using classification algorithms from five different families. In all cases, classification accuracy was benefited from using CSP instead of FDTW, LPC, PCA or ICA for feature extraction. Particularly with the combination CSP-Naïve Bayes we obtained the best average precision of 84.63%.     

肿瘤临床治疗中应关注肝脏

抗肿瘤细胞毒性药物有不同程度毒副作用,有些严重毒副反应是限制药物剂量或使用的直接原因。肝脏是药物代谢的主要器官,也是药物损伤的主要靶器官。随着临床肿瘤治疗关注治疗带来的副作用与关注疗效同等重要的发展,本文对抗肿瘤细胞毒性药物与肝损伤、发生机制、诊断、分型和临床治疗进展进行了阐述。     

Anticipatory attention during the sleep onset period

To examine whether anticipatory attention or expectancy is a cognitive process that is automatic or requires conscious control, we employed a paired-stimulus event-related potential (ERP) paradigm during the transition to sleep. The slow negative ERP wave observed between two successive stimuli, the Contingent Negative Variation (CNV), reflects attention and expectancy to the second stimulus. Thirteen good sleepers were instructed to respond to the second stimulus in a pair during waking sessions. In a non-response paradigm modified for sleep, participants then fell asleep while tones played. As expected, N1 decreased and P2 increased in amplitude systematically with the loss of consciousness at sleep onset; the CNV was increasingly more positive. Sleep onset latency was correlated with the amplitude of the CNV. The systematic attenuation of the CNV waveform at sleep onset and its absence in sleep indicates that anticipatory attention requires endogenous conscious control.