Outliers are observations or measures that are suspicious because they are much smaller or much larger than the vast majority of the observations. These observations are problematic because they may not be caused by the mental process under scrutiny or may not reflect the ability under examination. The problem is that a few outliers is sometimes enough to distort the group results (by altering the mean performance, by increasing variability, etc.). In this paper, various techniques aimed at detecting potential outliers are reviewed. These techniques are subdivided into two classes, the ones regarding univariate data and those addressing multivariate data. Within these two classes, we consider the cases where the population distribution is known to be normal, the population is not normal but known, or the population is unknown. Recommendations will be put forward in each case.

Effect sizes and confidence intervals are important statistics to assess the magnitude and the precision of an effect. The various standardized effect sizes can be grouped in three categories depending on the experimental design: measures of the difference between two means (the d family), measures of strength of association (e.g., r, R 2 , η 2 , ω 2), and risk estimates (e.g., odds ratio, relative risk, phi; Kirk, 1996). Part I of this study reviews the d family, with a special focus on Cohen's d and Hedges' g for two-independent groups and two-repeated measures (or paired samples) designs. The present paper answers questions concerning the d family via Monte Carlo simulations. First, four different denominators are often proposed to standardize the mean difference in a repeated measures design. Which one should be used? Second, the literature proposes several approximations to estimate the standard error. Which one most closely estimates the true standard deviation of the distribution? Lastly, central and noncentral methods have been proposed to construct a confidence interval around d. Which method leads to more precise coverage, and how to calculate it? Results suggest that the best way to standardize the effect in both designs is by using the pooled standard deviation in conjunction with a correction factor to unbias d. Likewise, the best standard error approximation is given by substituting the gamma function from the true formula by its approximation. Lastly, results from the confidence interval simulations show that, under the normality assumption, the noncentral method is always superior, especially with small sample sizes. However, the central method is equivalent to the noncentral method when n is greater than 20 in each group for a between-group design and when n is greater than 24 pairs of observations for a repeated measures design. A practical guide to apply the findings of this study can be found after the general discussion.

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SUMMARY The radiometric enzymatic technique of Coyle andHenry (J. Neurochem. 21: 61-67, 1973) was adapted to the measurement of serum catecholamines. This technique requires less time than other enzymatic techniques and is sensitive to quantities as small as 25 pg. In normotensive subjects lying supine for 20 minutes serum catecholamine levels averaged 0.218 ng/ml, with no obvious sex or age difference. Under these standardized conditions, the circulating catecholamine levels for a given individual are highly reproducible on different days over a period of several months. In 22 patients with essential hypertension, circulating levels were significantly higher, with an average of 0.370 ng/ml. More than 50% of the hypertensive patients had values greater than the highest value measured in normotensives. Systolic blood pressure and heart rate were significantly higher in the hypertensive group with elevated levels of circulating catecholamines than in the hypertensive group with normal levels. In one model of experimental hypertension, produced in the rat by administration of deoxycorticosterone acetate (DOCA) and saline for 4-8 weeks, serum catecholamines were significantly elevated. These findings suggest that the sympathetic system may play an important role in maintaining an elevated blood pressure in experimental hypertension and in a significant proportion of patients with essential hypertension.BECAUSE OF the poor sensitivity of available fluorometric techniques and the low concentrations of circulating catecholamines, fluorometric measurements of these amines have yielded variable results.1 In recent years the introduction of a highly sensitive enzymatic double-isotope technique for the determination of plasma catecholamines has made possible a more accurate estimation of these amines.2 More recently, Coyle and Henry 3 have reported a method for the differential determination of catecholamines and dopamine in tissues. Their technique, based on the same principle as that of Engelman and Portnoy, 2 is more sensitive and considerably less time-consuming than the latter. Although this technique is applicable to small pieces of tissue, it cannot be used on plasma or serum because of the presence of an inhibitor of the activity of catechol 0-methyl transferase (COMT), which is required to convert the catecholamines into tritiated O-methylated compounds in presence of s H-5-adenosine methionine. In our study we modified the technique of Coyle and Henry to prevent the inhibition of COMT. This modified technique can be used to measure, with a high degree of sensitivity, catecholamines in small quantities of serum.Using this technique, we studied serum catecholamines in an experimental model of hypertension as well as in patients with essential hypertension. Our results suggest that circulating catecholamines may play an important role in the development and maintenance of hypertension induced by deoxycorticosterone acetate (DOCA) and sodium. Moreover, it appears that a significant proportion of hypertensive patients...