Development of the Nine-Ball Skills Test to discriminate elite and high-level amateur golfers

Currently, there is a lack of appropriate skill assessments available for use in golf. The aim of this study was to examine the discriminative validity and the test-retest reliability of the newly developed "Nine-Ball Skills Test". Participants of two ability levels (elite, n = 14; high-level amateur, n = 16) each hit nine golf shots of differing combinations of trajectory (straight, fade, draw) and height (normal, high, low) at an individually determined target area. Each shot was scored on its percent error index from the target and whether it achieved the maximum height as required. Participants completed the test twice using a 5-iron club. The elite group scored significantly higher (P < 0.05) than the amateur group for both the first and second rounds of the test as well as the combined scores. The between-round test-retest reliability was deemed to be not acceptable, thus we propose that the test's protocol should include use of the two rounds as standard. Due to the importance of ball striking and flight control to performance in golf, the Nine-Ball Skills Test is appropriate for providing a measure of this skill component in elite and high-level amateur golfers.     

Exploratory analyses to improve model fit: Errors due to misspecification and a strategy to reduce their occurrence

Two Lagrange multiplier (LM) methods may be used in specification searches for adding parameters to models: one based on univariate LM tests and respecification of the model (LM‐respecified method) and the other based on a partitioning of multivariate LM tests (LM‐incremental method). These methods may result in extraneous parameters being included in models due to either sampling error or the model being misspecified. A 2‐stage specification search may be used to reduce errors due to misspecification. In the 1st stage, parameters are added to models based on LM tests to maximize fit. Second, parameters added in the 1st stage are deleted if they are no longer necessary to maintain model fit. Illustrations are presented to demonstrate that errors due to misspecification occur with the LM‐respecified method and are even more likely with the LM‐incremental approach. These illustrations also show how the deletion stage can help eliminate some of these errors.     

The relationship between inertial measurement unit-derived ‘force signatures’ and ground reaction forces during cricket pace bowling

Abstract

This study assessed the reliability and validity of segment measured accelerations in comparison to front foot contact (FFC) ground reaction force (GRF) during the delivery stride for cricket pace bowlers. Eleven recreational bowlers completed a 30-delivery bowling spell. Trunk- and tibia-mounted inertial measurement units (IMUs) were used to measure accelerations, converted to force, for comparisons to force plate GRF discrete measures. These measures included peak force, impulse and the continuous force–time curve in the vertical and braking (horizontal) planes. Reliability and validity was determined by intra-class correlation coefficients (ICC), coefficient of variation (CV), Bland–Altman plots, paired sample t-tests, Pearson’s correlation and one-dimensional (1D) statistical parametrical mapping (SPM). All ICC (0.90–0.98) and CV (4.23–7.41%) were acceptable, except for tibia-mounted IMU braking peak force (CV = 12.44%) and impulse (CV = 18.17%) and trunk vertical impulse (CV = 17.93%). Bland–Altman plots revealed wide limits of agreement between discrete IMU force signatures and force plate GRF. The 1D SPM outlined numerous significant (p < 0.01) differences between trunk- and tibia-located IMU-derived measures and force plate GRF traces in vertical and braking (horizontal) planes. The trunk- and tibia-mounted IMUs appeared to not represent the GRF experienced during pace bowling FFC when compared to a gold-standard force plate.     

The Interparental Relationship and Family Problem Solving with Preadolescent Males

This study examines associations between the quality of the interparental relationship and how well 68 family triads (mother, father, preadolescent son) solved salient problems which arose at home. Four aspects of the interparental relationship (marital satisfaction, parental agreement, conflict during family problem solving, and parental coalitions) were included in a regression analysis which controlled for family structure and child externalizing. A longitudinal design assessed families when mean child age was 9.7 years and 2 years later. Parental agreement consistently facilitated family problem solving. However, strong parental coalitions inhibited family problem solving, which may be attributed to frustrated autonomy needs of preadolescent males in response to the parental coalition. Stepfamilies had less effective problem solving at Time 1. The results confirm the benefits of parental agreement to child outcomes via enhanced family problem solving but show a reverse effect when agreement occurs in the context of coalitions against a preadolescent son.     

Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods

A number of psychometricians have suggested that parallel analysis (PA) tends to yield more accurate results in determining the number of factors in comparison with other statistical methods. Nevertheless, all too often PA can suggest an incorrect number of factors, particularly in statistically unfavorable conditions (e.g., small sample sizes and low factor loadings). Because of this, researchers have recommended using multiple methods to make judgments about the number of factors to extract. Implicit in this recommendation is that, when the number of factors is chosen based on PA, uncertainty nevertheless exists. We propose a Bayesian parallel analysis (B-PA) method to incorporate the uncertainty with decisions about the number of factors. B-PA yields a probability distribution for the various possible numbers of factors. We implement and compare B-PA with a frequentist approach, revised parallel analysis (R-PA), in the contexts of real and simulated data. Results show that B-PA provides relevant information regarding the uncertainty in determining the number of factors, particularly under conditions with small sample sizes, low factor loadings, and less distinguishable factors. Even if the indicated number of factors with the highest probability is incorrect, B-PA can show a sizable probability of retaining the correct number of factors. Interestingly, when the mode of the distribution of the probabilities associated with different numbers of factors was treated as the number of factors to retain, B-PA was somewhat more accurate than R-PA in a majority of the conditions.