Factor-type estimators of population mean are applicable to where correlations between the study and auxiliary variables are positive or negative. Their efficiency depends on the optimum estimate of the value of positive real number which is usually a function of the study and auxiliary variables. However, existing factor-type estimators are found not to be defined for some values of d and some have lower precision for positive correlation coefficient . This study aimed at modifying some conventional factor-type estimators under single-phase and two-phase sampling schemes by incorporating more information on auxiliary variables like coefficients of skewness ( ), kurtosis ( ), variation ( ) and standard deviation ( ) to produce more efficient ones. The specific objectives of this study were to: (i) obtain four modified factor-type estimators under single and two-phase sampling; (ii) derive the Biases and Mean Square Errors (MSEs) of these modified factor-type estimators; (iii) derive the conditions under which these modified estimators will be more efficient than the conventional ones; (iv) determine the relative efficiency of these modified estimators using both real life and simulated data; and (v) determine the robustness of these modified factor-type estimators under super-population and non-response model.rnThe four modified estimators under single-phase and two-phase sampling schemes considered are: , , and . These are done by incorporating more information on auxiliary variables like coefficients of skewness ( ), kurtosis ( ), variation ( ) and standard deviation ( ) to produce more efficient ones.rnrnThe findings were: rni. four modified factor-type estimators for population mean were obtained;rnii. Biases and MSEs of these modified factor-type estimators were theoretically and empirically derived;rniii. conditions under which these modified estimators were more efficient were derived;rniv. using both real life and simulated data, the modified factor-type estimators were found to have lower Mean Square Errors and highest relative efficiency, hence more efficient than the conventional ones; andrnv. the four modified estimators demonstrated high level of robustness under super-population and non-response models in comparison to the conventional ones.rnThis study concluded that when: (i). (ii). (iii). and (iv). , these modified factor-type estimators are better than the existing ones where, while , and are the correlation coefficients between x and y, x and z and, y and z respectively . Therefore, these modified estimators are recommended for use in estimating finite population mean in sample survey.