%0 Journal Article %1 Avery2003 %A Avery, Lisa M %A Russell, Dianne J %A Raina, Parminder S %A Walter, Stephen D %A Rosenbaum, Peter L %D 2003 %J Arch Phys Med Rehabil %K Algorithms; Analysis of Variance; Cerebral Palsy; Child; Child Development; Child, Preschool; Cross-Sectional Studies; Data Interpretation, Statistical; Decision Trees; Female; Humans; Infant; Likelihood Functions; Longitudinal Male; Motor Skills; Ontario; Psychometrics; Severity Illness Index %N 5 %P 697--705 %T Rasch analysis of the Gross Motor Function Measure: validating the assumptions of the Rasch model to create an interval-level measure. %V 84 %X OBJECTIVES: To describe the Rasch analysis of the Gross Motor Function Measure (GMFM-88) and to demonstrate how the assumptions of unidimensionality, sample-free measurement, and test-free measurement were validated to create an interval level measure. DESIGN: Cross-sectional and longitudinal (12-mo) data from a prospective study of motor development in children with cerebral palsy (CP) were used for the analysis. SETTING: Motor assessments were completed at 18 children's ambulatory rehabilitation centers in Ontario, Canada, by pediatric physical therapists trained in the use of the GMFM-88. PARTICIPANTS: The first 537 of 682 children enrolled into a longitudinal study of motor development in children with CP. Children had a mean age of 6.43+/-2.75 years (range, 11mo-12y) with varying types and severity of CP. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: The GMFM-88. RESULTS: The Rasch analysis, in conjunction with clinical decisions, identified 66 items from the GMFM-88 that formed a unidimensional measure (GMFM-66). Assumptions of sample-free and test-free measurement were confirmed, and a user-friendly scoring program was developed. CONCLUSIONS: The GMFM-66 is an interval-level measure of gross motor function for children with CP; it should improve the scoring, interpretation, and overall clinical and research utility over the original GMFM.

@article{Avery2003, abstract = {OBJECTIVES: To describe the Rasch analysis of the Gross Motor Function Measure (GMFM-88) and to demonstrate how the assumptions of unidimensionality, sample-free measurement, and test-free measurement were validated to create an interval level measure. DESIGN: Cross-sectional and longitudinal (12-mo) data from a prospective study of motor development in children with cerebral palsy (CP) were used for the analysis. SETTING: Motor assessments were completed at 18 children's ambulatory rehabilitation centers in Ontario, Canada, by pediatric physical therapists trained in the use of the GMFM-88. PARTICIPANTS: The first 537 of 682 children enrolled into a longitudinal study of motor development in children with CP. Children had a mean age of 6.43+/-2.75 years (range, 11mo-12y) with varying types and severity of CP. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: The GMFM-88. RESULTS: The Rasch analysis, in conjunction with clinical decisions, identified 66 items from the GMFM-88 that formed a unidimensional measure (GMFM-66). Assumptions of sample-free and test-free measurement were confirmed, and a user-friendly scoring program was developed. CONCLUSIONS: The GMFM-66 is an interval-level measure of gross motor function for children with CP; it should improve the scoring, interpretation, and overall clinical and research utility over the original GMFM.}, added-at = {2014-07-19T17:50:12.000+0200}, author = {Avery, Lisa M and Russell, Dianne J and Raina, Parminder S and Walter, Stephen D and Rosenbaum, Peter L}, biburl = {https://www.bibsonomy.org/bibtex/2fc2b1977489a3bc134e8a67da089378c/ar0berts}, groups = {public}, interhash = {9308c5f51af39f7864a6f788f7f03e1a}, intrahash = {fc2b1977489a3bc134e8a67da089378c}, journal = {Arch Phys Med Rehabil}, keywords = {Algorithms; Analysis of Variance; Cerebral Palsy; Child; Child Development; Child, Preschool; Cross-Sectional Studies; Data Interpretation, Statistical; Decision Trees; Female; Humans; Infant; Likelihood Functions; Longitudinal Male; Motor Skills; Ontario; Psychometrics; Severity Illness Index}, month = May, number = 5, pages = {697--705}, pii = {S0003999303048962}, pmid = {12736885}, timestamp = {2014-07-19T17:50:12.000+0200}, title = {Rasch analysis of the Gross Motor Function Measure: validating the assumptions of the Rasch model to create an interval-level measure.}, username = {ar0berts}, volume = 84, year = 2003 }