The principal axis method is a method for extracting factors in EFA that uses only the expected variance of the variables, i.e., the variance that is shared by two or more variables. It assumes that each variable has some measurement error or unique variance that is not explained by the factors. The maximum likelihood method is another method for extracting factors in EFA that uses all the variance of the variables, i.e., both standard and unique variance. It assumes that each variable has no measurement error or unique variance that is not explained by the factors. To use these methods in EFA in R, we can use the psych::fa() function, which provides various options for extraction methods, such as minres (minimum residual), ml (maximum likelihood), pa (principal axis), etc.