https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1108&context=usepapapers

Receptor modeling application framework for particle source apportionment.

How do we measure phenomena that cannot be directly observed? The principal aim of this paper is to demonstrate why factor analysis technique is the best answer to this question. Methodologically, we use a database with different indicators of democracy to show how principal component analysis can be employed to measure the two polyarchy dimensions proposed by Robert Dahl (1971): contestation and inclusiveness. On substantive grounds, we hope to facilitate the understanding of factor analysis technique in Social Sciences in general and in Political Science in particular.

/pdf/visao-alem-do-alcance-uma-introducao-a-analise-fatorial-brbl3wi6z4.pdf

Visão além do alcance: uma introdução à análise fatorial

This study extends evidence on the efficiency of stock markets in developing countries using data from the Nairobi Stock Exchange (NSE). Previous evidence from studies on stock markets in developing countries, and NSE in particular, is inconclusive. In many cases, the findings have not supported the random walk hypothesis and are therefore not consistent with efficiency in the weak-form. The key question investigated is whether successive share price returns on the Nairobi Stock Exchange are independent random variables so that price returns cannot be predicted from historical price returns. This study uses the traditional random walk methodology of serial correlation and runs tests as applied by Fama (1965), Cooper (1982), and Taylor (1986) rather than the newer methodologies of variance ratios [Lo and MacKinlay (1988)] and of regression [Jegadeesh (1990)]. These techniques are used for reasons of triangulation in research and for their intuitive appeal. They remain appropriate tools for testing the weak-form EMH despite challenge from newer methodologies. In their use, nevertheless, the study recognises and deals with two largely ignored issues in their application to EMH tests in emerging markets: the quality and quantity of data, and the depth of analysis of the market microstructure. The quality and quantity of data are improved through the creation of a computer database. The study then analyses all three price series on the exchange: The Bid, Ask and Transaction prices. The findings suggests that with proper control over the quality of the data and the use of a larger number of data observations, the random walk model can be a good description of successive price returns in an emerging stock market. This has been shown to hold irrespective of whether bid, ask, or transaction returns are used. This is contrary to most of the earlier evidence that the random walk model does not apply in such markets. The results obtained are therefore consistent with the weak-form of the EMH.

Market efficiency in developing countries: a case study of the nairobi stock exchange

Return predictability in African stock markets

Summary

Despite decades of sleep research by means of polysomnography (PSG), systematic interindividual differences in PSG-assessed sleep parameters have been scarcely investigated. The present study is the first to quantify interindividual variability in standard PSG-assessed variables of sleep structure in terms of stability and robustness as well as magnitude. Twenty-one carefully screened healthy young adults were studied continuously in a strictly controlled laboratory environment, where their PSGs were recorded for eight nights interspersed with three separate 36 h sleep deprivation periods. All PSG records were scored blind to subject and condition, using conventional criteria, and delta power in the non-REM sleep EEG was computed for four electrode derivations. Interindividual differences in sleep variables were examined for stability and robustness, respectively, by comparing results across equivalent nights (e.g. baseline nights) and across experimentally differentiated nights (baseline nights versus recovery nights following sleep deprivation). Among 18 sleep variables analyzed, all except slow-wave sleep (SWS) latency were found to exhibit significantly stable and robust – i.e. trait-like – interindividual differences. This was quantified by means of intraclass correlation coefficients (ICCs), which ranged from 36% to 89% across physiologic variables, and were highest for SWS (73%) and delta power in the non-REM sleep EEG (78–89%). The magnitude of the trait interindividual differences was considerable, consistently exceeding the magnitude of the group-average effect on sleep structure of 36 h total sleep deprivation. Notably, for non-REM delta power – a putative marker of sleep homeostasis – the interindividual differences were from 9.9 to 12.8 times greater than the group-average increase following sleep deprivation relative to baseline. Physiologic sleep variables did not vary among subjects in a completely independent manner – 61.1% of their combined variance clustered in three trait dimensions, which appeared to represent sleep duration, sleep intensity, and sleep discontinuity. Any independent functional significance of these sleep physiologic phenotypes remains to be determined.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2869.2007.00594.x

Trait interindividual differences in the sleep physiology of healthy young adults

(1982). World stock markets: some random walk tests. Applied Economics: Vol. 14, No. 5, pp. 515-531.

World stock markets: some random walk tests

The basic underlying theory of factor analysis is presented and the results of an empirical study are reproduced and interpreted to illustrate application of the technique.

John C. B. Cooper

Papers

World stock markets: some random walk tests

Factor Analysis: An Overview