Repeated measures correlation (rmcorr) is a statistical technique for determining the common within-individual association for paired measures assessed on two or more occasions for multiple individuals. Simple regression/correlation is often applied to non-independent observations or aggregated data; this may produce biased, specious results due to violation of independence and/or differing patterns between-participants versus within-participants. Unlike simple regression/correlation, rmcorr does not violate the assumption of independence of observations. Also, rmcorr tends to have much greater statistical power because neither averaging nor aggregation is necessary for an intra-individual research question. Rmcorr estimates the common regression slope, the association shared among individuals. To make rmcorr accessible, we provide background information for its assumptions and equations, visualization, power, and tradeoffs with rmcorr compared to multilevel modeling. We introduce the R package (rmcorr) and demonstrate its use for inferential statistics and visualization with two example datasets. The examples are used to illustrate research questions at different levels of analysis, intra-individual, and inter-individual. Rmcorr is well-suited for research questions regarding the common linear association in paired repeated measures data. All results are fully reproducible.

Repeated measures correlation (rmcorr) is a statistical technique for determining the common within-individual association for paired measures assessed on two or more occasions for multiple individuals. Simple regression/correlation is often applied to non-independent observations or aggregated data; this may produce biased, specious results due to violation of independence and/or differing patterns between-participants versus within-participants. Unlike simple regression/correlation, rmcorr does not violate the assumption of independence of observations. Also, rmcorr tends to have much greater statistical power because neither averaging nor aggregation is necessary for an intra-individual research question. Rmcorr estimates the common regression slope, the association shared among individuals. To make rmcorr accessible, we provide background information for its assumptions and equations, visualization, power, and tradeoffs with rmcorr compared to multilevel modeling. We introduce the R package (rmcorr) and demonstrate its use for inferential statistics and visualization with two example datasets. The examples are used to illustrate research questions at different levels of analysis, intra-individual, and inter-individual. Rmcorr is well-suited for research questions regarding the common linear association in paired repeated measures data. All results are fully reproducible.

Repeated measures correlation (rmcorr) is a statistical technique for determining the common within-individual association for paired measures assessed on two or more occasions for multiple individuals. Simple regression/correlation is often applied to non-independent observations or aggregated data; this may produce biased, specious results due to violation of independence and/or differing patterns between-participants versus within-participants. Unlike simple regression/correlation, rmcorr does not violate the assumption of independence of observations. Also, rmcorr tends to have much greater statistical power because neither averaging nor aggregation is necessary for an intra-individual research question. Rmcorr estimates the common regression slope, the association shared among individuals. To make rmcorr accessible, we provide background information for its assumptions and equations, visualization, power, and tradeoffs with rmcorr compared to multilevel modeling. We introduce the R package (rmcorr) and demonstrate its use for inferential statistics and visualization with two example datasets. The examples are used to illustrate research questions at different levels of analysis, intra-individual, and inter-individual. Rmcorr is well-suited for research questions regarding the common linear association in paired repeated measures data. All results are fully reproducible.

Performance affects the perceived size of an action's target. For example, softball players who are hitting well judge the ball to be bigger than do players who have more difficulty hitting . The notion that action-related information such as performance levels affects perception challenges many past and current theories of perception (e.g., Fodor, 1983;Pylyshyn, 2003). Most theories consider perception to be an encapsulated process that is informed solely by optical information and oculomotor adjustments. However, a growing body of research demonstrates that action abilities affect perceived size (Wesp, Cichello, Gracia, & Davis, 2004;, distance (Proffitt, Stefanucci, Banton, & Epstein, 2003; Witt & Proffitt, in press;Witt, Proffitt, & Epstein, 2004, and geographical slant (Bhalla & Proffitt, 1999).In a study on softball players , we found a significant correlation between batting average for the game or games played on that night and judged ball size. Players who had hit well recalled the size of the softball to be bigger than did those who hit less well, thereby suggesting a relationship between perception and performance. However, a question remains as to who really sees the ball as bigger. It could be the people who are more accomplished players, or it could be the people who played better on that night. This question addresses the nature of the effects of performance on perception. These effects might be time dependent, in which case only players who are playing well at the moment will see the ball as bigger, or the effect might be quite general, in which case better players always see the ball as bigger, independent of how they are playing at any given time.To better understand the effects of performance on perception, we conducted a similar experiment with golfers. Golfers often comment on how their perception of the hole varies with performance. Anecdotal and highly exaggerated comments found in the sport's press suggest that on good days, the hole can look as big as a bucket or a basketball hoop. On bad days, the hole can look as small as a dime, an aspirin, or the inside of a donut. The optical information received by the eye is obviously the same regardless of how well golfers are playing, so do golfers really see the hole differently depending on their performance? And if so, is the effect due to their performance on that day or to their general abilities to play golf? Either way, the results would suggest that the perceived capacity to successfully perform a goal-oriented action can influence how big the target looks. EXPERIMENT 1We recruited golfers after they played a round of golf and asked them to estimate the size of the hole. We also collected information on how well they played that day, and found correlations between performance and apparent hole size. MethodParticipants. Forty-six golfers (1 female; age range 26-66, mean age 45.9) at the Providence Golf Club in Richmond, VA, agreed to participate. All gave informed consent.Stimuli. Nine black paper circles were glued to a piece of white p...

Previous research has suggested that perceived distances are scaled by the action capabilities of the body. The present studies showed that when reachability is constrained due to a difficult grasp to pick up an object, perceived distance to the object increases. Participants estimated the distances to tools whose orientations made them either easy or difficult to grasp with their dominant and non-dominant hands. Right-handed participants perceived tools that were more difficult to grasp to be farther away than tools that were easier to grasp. However, perceived distance did not differ in left-handed participants. These studies suggest that when reaching to a target, the distance to that target is scaled in terms of how far one can effectively reach given the type of reaching posture that is executed. Furthermore, this effect is modulated by handedness.

Perception of one's body is related not only to the physical appearance of the body, but also to the neural representation of the body. The brain contains many body maps that systematically differ between right-and left-handed people. In general, the cortical representations of the right arm and right hand tend to be of greater area in the left hemisphere than in the right hemisphere for righthanded people, whereas these cortical representations tend to be symmetrical across hemispheres for left-handers. We took advantage of these naturally occurring differences, and examined perceived arm length in right-and left-handed people. When looking at each arm and hand individually, right-handed participants perceived their right arms and right hands to be longer than their left arms and left hands, whereas left-handed participants perceived both arms accurately. These experiments reveal a possible relationship between implicit body maps in the brain and conscious perception of the body.When people look at their bodies, what they see is likely influenced by the neural representation of the body in the cortex, and is not solely due to the way the body appears physically. Right-handed individuals have asymmetric neural representations of the bodythere is typically more cortical area and higher neural activation associated with the right arm and hand than with the left arm and hand-whereas left-handed individuals usually have near-symmetrical cortical body representations (Kim et al., 1993;Sörös et al., 1999;Zilles et al., 1997). Extending this finding, the current studies assessed whether asymmetries in cortical representation would be related to the perceived size of the associated body part. To obtain disparities in the sizes of cortical areas, we took advantage of naturally occurring individual differences associated with handedness. If the extent of neural body representation is predictive of the perceived size of the body, then right-handed people should perceive their right arm to be longer than their left arm, and left-handed people should perceive the right and left arms as being the same length. Among right-handed participants, we found these anticipated asymmetries in perceived arm length and hand size, as well as in perceived reaching ability and grasping ability. In contrast, perceived arm length and anticipated reach were symmetrical for left-handed participants, paralleling the symmetries in their cortical representations. These findings provide compelling evidence for the hypothesis that neural body representations are reflected in how people visually perceive their bodies.

Given the high volume of available and shared information and the safety-critical and time-sensitive nature of many decisions, these results have implications for training and system design in C2 domains. To avoid decrements to SA, interpersonal trust, and decision-making performance, information presentation within C2 systems must reflect human cognitive processing limits and capabilities.

Many amateur athletes believe that using a professional athlete's equipment can improve their performance. Such equipment can be said to be affected with positive contagion, which refers to the belief of transference of beneficial properties between animate persons/objects to previously neutral objects. In this experiment, positive contagion was induced by telling participants in one group that a putter previously belonged to a professional golfer. The effect of positive contagion was examined for perception and performance in a golf putting task. Individuals who believed they were using the professional golfer's putter perceived the size of the golf hole to be larger than golfers without such a belief and also had better performance, sinking more putts. These results provide empirical support for anecdotes, which allege that using objects with positive contagion can improve performance, and further suggest perception can be modulated by positive contagion.