4 resultados para Experimental Testing

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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Regular stair climbing has well-documented health dividends, such as increased fitness and strength, weight loss and reduced body fat, improved lipid profiles and reduced risk of osteoporosis. The general absence of barriers to participation makes stair climbing an ideal physical activity (PA) for health promotion. Studies in the US and the UK have consistently shown that interventions to increase the accumulation of lifestyle PA by climbing stairs rather than using the escalators are effective. However, there are no previous in Catalonia. This project tested one message for their ability to prompt travelers on the Montjuïc site to choose the stairs rather than the escalator when climbing up the Monjuïc hill. One standard message, " Take the stairs! 7 minutes of stair climbing a day protects your heart" provided a comparison with previous research done in the UK. Translated into Catalan and Spanish, it was presented on a poster positioned at the point of choice between the stairs and the escalator. The study used a quasi-experimental, interrupted time series design. Travelers, during several and specific hours on two days of the week, were coded for stair or escalator use, gender, age, ethnic status, presence of accompanying children or bags by one observer. Overall, the intervention resulted in a 81% increase in stair climbing. In the follow-up period without messages, stair climbing dropped out to baseline levels. This preliminary study showed a significant effect on stair use. However, caution is needed since results are based on a small sample and, only a low percentage of the sample took the stairs at baseline or the intervention phase . Future research on stair use in Catalonia should focus on using bigger samples, different sites (metro stations, airports, shopping centers, etc) , different messages and techniques to promote stair climbing.

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We examine the effect of unilateral and mutual partner selection in the context of prisoner's dilemmas experimentally. Subjects play simultaneously several finitely repeated two-person prisoner's dilemma games. We find that unilateral choice is the best system. It leads to low defection and fewer singles than with mutual choice. Furthermore, with the unilateral choice setup we are able to show that intendingdefectors are more likely to try to avoid a match than intending cooperators. We compare our results of multiple games with single game PD-experiments and find no difference in aggregate behavior. Hence the multiple game technique is robust and might therefore be an important tool in the future for testing the use of mixed strategies.

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The present work focuses the attention on the skew-symmetry index as a measure of social reciprocity. This index is based on the correspondence between the amount of behaviour that each individual addresses to its partners and what it receives from them in return. Although the skew-symmetry index enables researchers to describe social groups, statistical inferential tests are required. The main aim of the present study is to propose an overall statistical technique for testing symmetry in experimental conditions, calculating the skew-symmetry statistic (Φ) at group level. Sampling distributions for the skew- symmetry statistic have been estimated by means of a Monte Carlo simulation in order to allow researchers to make statistical decisions. Furthermore, this study will allow researchers to choose the optimal experimental conditions for carrying out their research, as the power of the statistical test has been estimated. This statistical test could be used in experimental social psychology studies in which researchers may control the group size and the number of interactions within dyads.

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In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is studied. The performance of the ten lag-one autocorrelation estimators is compared in terms of Mean Square Error (combining bias and variance) using data series generated by Monte Carlo simulation. The results show that there is not a single optimal estimator for all conditions, suggesting that the estimator ought to be chosen according to sample size and to the information available of the possible direction of the serial dependence. Additionally, the probability of labelling an actually existing autocorrelation as statistically significant is explored using Monte Carlo sampling. The power estimates obtained are quite similar among the tests associated with the different estimators. These estimates evidence the small probability of detecting autocorrelation in series with less than 20 measurement times.