ประสิทธิภาพของการประมาณค่าพารามิเตอร์และดัชนีวัดความสอดคล้องเชิงประจักษ์ในการวิเคราะห์องค์ประกอบเชิงยืนยันภายใต้โมเดลระบุผิดพลาดและตัวแปรสังเกตได้มีการแจกแจงไม่ปกติ - กันตินันท์ นันทนาดิศัย (จุฬาลงกรณ์มหาวิทยาลัย, 2016)
This research objectives were to study parameter estimation methods efficiency and efficiency of empirical fit indices in confirmatory factor analysis under no misspecification model and misspecification model with nonnormality observed variables. Data were generated by using Monte Carlo technique under 576 conditions from five factors included (1) three types of parameter misspecification included latent variable covariances, factor loadings, measurement error covariances (2) four levels of misspecification included no misspecification (RMSEA=.000), low (RMSEA=.02), moderate (RMSEA=.04), and high (RMSEA=.06) (3) three observe variable distributions included low platykurtic (ku=-1), moderate leptokurtic (ku=1) and high leptokurtic (ku=2) (4) four sample sizes included 200, 400, 600 and 800 (5) four parameter estimation methods include maximum likelihood (ML), robust maximum likelihood (RML), generalized least squares (GLS), and weighted least squares (WLS). Each condition was repeated 1000 times. The sensitivity relative biased (RB), Coefficient of variation (CV), type I error and power of the test were used as criteria for the efficiency of parameter estimation methods and empirical fit indices. The research results were: (1) ML and RML methods were most efficient and had equal RB. RML method had more efficiency of CV than ML, GLS and WLS methods in both no misspecification model and misspecification model. Level of misspecification was most effected to RB and type of parameter was most effected to CV. (2) p-value, CFI, GAMMA, MC, RMSEA and TLI were large sensitive to misspecification and small to moderate sensitive to other extraneous variables. In case of no misspecification model, GAMMA index from all estimations can controlled type I error and in case of misspecification model p-value from ML and RML, CFI and TLI from GLS and WLS had more conditions of power of the test above 80 percent more than other indices.