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Direct linkMcNeish, Daniel – Journal of Experimental Education, 2018
Small samples are common in growth models due to financial and logistical difficulties of following people longitudinally. For similar reasons, longitudinal studies often contain missing data. Though full information maximum likelihood (FIML) is popular to accommodate missing data, the limited number of studies in this area have found that FIML…
Descriptors: Growth Models, Sampling, Sample Size, Hierarchical Linear Modeling
