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two that at rst seem close to 0 are revealed to be closer to 100 and support a largely bipolar structure (p 1029) To establish the validity of their claim, Green et al (1993) reported supportive ndings from several studies In discussing the results of their Study 1, for instance, they pointed out that an observed correlation of 25 was transformed into a latent correlation of 84 after controlling for error (see Green et al, 1993, p 1033) These seemingly impressive results have been interpreted by subsequent writers as establishing that raw, uncorrected correlations are highly distorted and can be expected to yield misleading results (Feldman Barrett & Russell, 1998; Russell & Carroll, 1999) Feldman Barrett and Russell (1998), for example, concluded that Green et al.

(1993) delivered the coup de gr ce to all research in which conclusions are based directly on the observed correlations between measures of affect (p 968; emphasis in original) However, as we document in detail elsewhere (see Watson & Clark, 1997; Watson & Tellegen, 1999; Watson et al, 1999), these critiques have substantially overestimated the actual effect of measurement error on mood ratings Indeed, corrected correlations will approach 100 only when the raw, uncorrected correlations already are quite substantial For instance, as noted earlier, Watson and Tellegen (1999) summarized the results of several studies that reported latent, corrected correlations between measures of Pleasantness and Unpleasantness; these correlations ranged from 84 to 93, with a median value of 91 It is noteworthy, however, that the mean uncorrected correlations ranged from 53 to 78 across these same studies, with a median value of .

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56 (see Watson & Tellegen, 1999, Table 1) Thus, the bipolarity of this dimension already is readily apparent in raw, uncorrected data, as we already observed in our own Table 141 (weighted mean r = 50) In contrast, measures of High Positive Affect and High Negative Affect had raw correlations ranging from 18 to 36, with a median value of 25; correcting them for measurement error yielded latent correlations ranging from 43 to 58 (Mdn = 46) More generally, analyses of this issue have established that controlling for measurement error can transform (a) low correlations into moderate correlations and (b) strong correlations into very strong correlations, but that it will not turn (c) low correlations into strong correlations (see Watson & Tellegen, 1999).

On the basis of these data, we can conclude that measurement error exerts only a moderate in uence on mood ratings, and that raw, uncorrected correlations do not yield highly distorted or misleading results This conclusion is unsurprising once one understands how these correlations are corrected for measurement error; we therefore will present a brief discussion of this topic Recent analyses of this issue (eg,.

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Perrig, W J, & Hofer, D (1989) Sensory and conceptual representations in memory: Motor images that cannot be imaged Psychological Research, 51, 201 207 Prinz, W (1997) Perception and action planning European Journal of Cognitive Psychology, 9, 129 154 Prinz, W (1998) Die reaktion als willenshandlung Psychologische Rundschau, 49(1), 10 20 Rosenbaum, D A, Hindorff, V, & Munro, E M (1987) Scheduling and programming of rapid finger sequences: Tests and elaborations of the hierarchical editor model Journal of Experimental Psychology: Human Perception and Performance, 13, 193 203 Rubinstein, S L (1964) Grundlagen der allgemeinen Psychologie Berlin: Verlag der Wissenschaften Rubinstein, S L (1984) Grundlagen der allgemeinen psychologie (10 Aufl) Berlin, Germany: Volk und Wissen Sackett, R S (1935) The relationship between amount of symbolic rehearsal and retention of a maze habit Journal of General Psychology, 13, 113 128 Saltzman, E (1979) Levels of sensorimotor representation.

Journal of Mathematical Psychology, 20, 91 163 Schack, T (1997) ngstliche sch ler im sport: Interventionsverfahren zur entwicklung der handlumgskontrolle Schorndorf, Germany: Hofmann Schack, T (2000) Experimental studies on the speed of information processing in sports-related memory Journal of Sport and Exercise Psychology, 22, 94 Schack, T (2002) Zur kognitiven architektur von bewegungshandlungen: Modelltheoretischer zugang und experimentelle untersuchungen Unver ff Habil, Psychologisches Institut, Deutsche Sporthochschule, K ln, Germany Schack, T (2003) The relationship between motor representation and biomechanical parameters in complex movements: Towards an integrative perspective of movement science European Journal of Sportscience, 3(2), 1 13 Schack, T (2004a) The cognitive architecture of complex movement International Journal of Sport and Exercise Psychology, 2(4), 403 438 Schack, T (2004b) Knowledge and performance in action Journal of Knowledge Management, 8(4), 38 53 Schack, T, & Bar-Eli, M (in press) Psychological factors in technical preparation In B Blumenstein & R.

Lidor (Eds), Psychology of sport training M nster, Germany: Meyer & Meyer Schack, T, & Garzke, P (2002) Neue wege im techniktraining im surfen Unpublished manuscript , Unver ff Deutsche Sporthochschule, K ln, Germany Schack, T, & Heinen, T (2000) Mental training based on mental representation In B A Carlsson, U Johnson, &.

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