Analysis of Means for Analyzing Missing Data from Experimental Designs – Part I
Keywords:
Analysis of Means, Missing Data, Latin Square Designs, Graeco Latin Square Designs, Hyper Graeco-Latin-Square DesignsAbstract
A step-by-step analysis of means (ANOM) procedure proposed by Subramani (1992) to analyze the missing data from randomized block designs has been extended to other experimental designs with several missing observations. The proposed method is general in nature. For the sake of simplicity the procedure of analysis of means to analyze missing data from experimental designs has been discussed in two parts. In part I, it is planned to apply this method for analyzing missing data from latin square designs, graeco latin square designs and hyper graeco latin square designs. The part II of this paper is dedicated to analyze the missing data from replicated latin square designs, cross over designs and F-Square designs. The procedure is also illustrated with the help of numerical examples.
Downloads
References
OTT. E.R.(1967: Analysis of Means – A Graphical Procedure, Industrial Quality Control, 24, 101-109.
SCHILLING, K.G. (1973): A Systematic Approach to Analysis of Means, Journal of Qaulity Technology, 5, 92-108,147-159
SUBRAMANI, J. (1991): Non-iterative Least Squares Estimation of Missing Values in Graeco-Latin Square Designs, Biometrical Journal, 33, 763-769.
SUBRAMANI, J. (1992): Analysis of Means for Experimental Designs with Missing Observations, Communi. In Statistics – Theory and Methods, 21, 2045-2057.
SUBRAMANI, J (1993): Non-interactive Least Squares Estimation of Missing Values In Hyper-Graeco-Latin Square Designs, Biometrical Journal, 35, 465-470.
SUBRAMANI, J. (1994): Non-iterative Least Squares Estimation of Missing Values In Cross-Over Designs without Residual Effect, Biometrical Journal, 36,285-292.
SUBRAMANI, J.and AGGARWAL, M.L. (1993): Estimation of several Missing values in F-Square Designs, Biometrical Journal, 35,455-463.
SUBRAMANI, J.and PONNUSWAMY, K.N. (1989): A Non-iterative Least Squares Estimation of Missing Values in Experimental Designs, Journal of Applied Statistics, 16, 77-86.
WILKINSON, G.N. (1958): Estimation of Missing Values for the Analysis of Incomplete Data, Biometrics, 14,257-286.
YATES, F. (1933): The Analysis of Replicated Experiments when the Field Results are Incomplete, Empire Journal of Experimental Agriculture,
