Group‐Randomized Trials, Planning and Analysis of

Murray, David M.

doi:10.1002/0471667196.ess7008

Cited by 184 publications

(304 citation statements)

References 4 publications

Supporting

Mentioning

299

Contrasting

Order By: Relevance

“…To compare injury rates, incidence rate ratios (IRRs) were obtained from Poisson regression models 27. Robust SEs were calculated to allow for randomisation by team 28. Intracluster correlations were calculated by comparing SEs from our analysis method with SEs from an analysis that ignored the clustering.…”

Section: Methodsmentioning

confidence: 99%

Head, face and neck injury in youth rugby: incidence and risk factors

et al. 2008

View full text Add to dashboard Cite

Objectives: In this study, the incidence of head, neck and facial injuries in youth rugby was determined, and the associated risk factors were assessed. Design: Data were extracted from a cluster randomised controlled trial of headgear with the football teams as the unit of randomisation. No effect was observed for headgear use on injury rates, and the data were pooled. Setting: General school and club-based community competitive youth rugby in the 2002 and 2003 seasons. Participants: Young male rugby union football players participating in under-13, under 15, under 18 and under 21 years competitions. Eighty-two teams participated in year 1 and 87 in year 2. Main outcome measures: Injury rates for all body regions combined, head, neck and face calculated for game and missed game injuries. Results: 554 head, face and neck injuries were recorded within a total of 28 902 h of rugby game exposure. Level of play and player position were related to injury risk. Younger players had the lowest rates of injury; forwards, especially the front row had the highest rate of neck injury; and inside backs had the highest rate of injuries causing the player to miss a game. Contact events, including the scrum and tackle, were the main events leading to injury. Conclusion: Injury prevention must focus on the tackle and scrum elements of a youth rugby game.Rugby union football is a popular international team sport played by both sexes and all age groups. In recent years, there has been a focus on the injury risks in professional rugby; however, the majority of rugby participants are not professional. [1][2][3][4] Internationally, there has been substantial interest in the causes and management of sporting head injuries. [5][6][7][8] There are unambiguous head and neck injury risks in rugby: head injury accounts for between 15% and 30% of all injury; 15% of injury cases are concussion; serious head injuries are rare; and spinal cord injury rates are very small, but of concern because of the resultant impairment.

show abstract

Section: Methodsmentioning

confidence: 99%

Head, face and neck injury in youth rugby: incidence and risk factors

et al. 2008

View full text Add to dashboard Cite

show abstract

“…Based upon previous research with the SDLMI, we determined an effect size in the moderate impact range (Cohen’s d = .38) and, along with an intra-class correlation (ρ) of .05 and baseline levels of self-determination as measured by The Arc’s Self-Determination Scale, conducted a power analysis using formulas specified by Murray (1998) and software, called Optimal Design, developed by Spybrook, Raudenbush, Liu, and Congdon (2006). Power analysis determined that we would need at least 26 schools with 12 students at each school to detect our effect in a completely balanced group randomized trial design.…”

Section: Methodsmentioning

confidence: 99%

“…We implemented a group-randomized, modified equivalent control group time series design (Murray, 1998) over two years to examine the impact of the SDLMI on self-determination. Project personnel contacted school districts, and districts that agreed to participate ( n = 20) identified high school campuses ( n = 39) to participate.…”

Section: Methodsmentioning

confidence: 99%

The Impact of the Self-Determined Learning Model of Instruction on Student Self-Determination

Wehmeyer

Shogren

Palmer

et al. 2012

Exceptional Children

188

115

View full text Add to dashboard Cite

Promoting self-determination has become best practice in special education. There remains, however, a paucity of causal evidence for interventions to promote self-determination. We conducted a group-randomized, modified equivalent control group design study of the efficacy of the Self-Determined Learning Model of Instruction to promote self-determination. Data on self-determination using multiple measures was collected with 312 high school students with cognitive disabilities in both a control and treatment group. We examined the relationship between the SDLMI and self-determination using structural equation modeling. After determining strong measurement invariance for each latent construct, we found significant differences in latent means across measurement occasions and differential effects attributable to the SDLMI. This was true across disability category, though there was variance across disability populations.

show abstract

“…As a result of this correlation, there is a lack of statistical independence across subjects. As independence is a critical assumption for sample size calculations and most other statistical analyses, it is likely that, in many cases, this assumption is violated 4–6 9. If each cluster comprises exposed and unexposed subjects, stratification for clusters can alleviate the clustering effect 5.…”

mentioning

confidence: 99%

Intracluster correlation coefficient in multicenter childhood trauma studies

Roudsari¹,

Fowler

Nathens

2007

Inj Prev

View full text Add to dashboard Cite

Objective: To calculate the intracluster correlation coefficient (ICC) for emergency department (ED) shock rate, early trauma death (ie, death during the first 24 h after arrival at hospital), and in-hospital trauma death rate for multicenter childhood injuries. Methods: The National Trauma Data Bank (5th revision), the largest multicenter trauma registry in the US, was used. Data from 80 trauma centers were used to calculate the ICC for in-hospital trauma death rate. Thirty three states provided data for calculation of the ICC for ED shock and early trauma death rate. Results: From 2000 to 2004, 13% of the 952 242 patients in the National Trauma Data Bank were ,15 years old. Approximately 17 000 of these children had injuries with an injury severity score .15, of whom 84% (14 095 subjects) were hospitalized at 80 level I or II trauma centers in 33 states. The ICCs for ED shock rate, early trauma death rate, and in-hospital death rate were 0.005 (95% CI 0.000 to 0.010), 0.014 (95% CI 0.004 to 0.024), and 0.023 (95% CI 0.013 to 0.033), respectively. These ICCs were calculated for boys and girls and also for blunt and penetrating injuries. Conclusion: Clustered childhood trauma studies that aim to compare different aspects of pre-hospital and hospital trauma care should incorporate these ICCs for sample calculation. When cluster randomized clinical trials are mounted, if sample sizes are calculated without adjustment for ICC, then the planned trial is likely to be seriously underpowered.

show abstract

Group‐Randomized Trials, Planning and Analysis of

Cited by 184 publications

References 4 publications

Head, face and neck injury in youth rugby: incidence and risk factors

Head, face and neck injury in youth rugby: incidence and risk factors

The Impact of the Self-Determined Learning Model of Instruction on Student Self-Determination

Intracluster correlation coefficient in multicenter childhood trauma studies

Contact Info

Product

Resources

About