polar                 package:psych                 R Documentation

_p_o_l_a_r :_c_o_n_v_e_r_t _C_a_r_t_e_s_i_a_n _f_a_c_t_o_r _l_o_a_d_i_n_g_s _i_n_t_o _p_o_l_a_r _c_o_o_r_d_i_n_a_t_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     Factor and cluster analysis output typically presents item by
     factor correlations (loadings).  Tables of factor loadings are
     frequently sorted by the size of loadings.  This style of
     presentation tends to make it difficult to notice the pattern of
     loadings on other, secondary, dimensions.  By converting to polar
     coordinates, it is easier to see the pattern of the secondary
     loadings.

_U_s_a_g_e:

     polar(f, sort = TRUE)

_A_r_g_u_m_e_n_t_s:

       f: A matrix of loadings or the output from a factor or cluster
          analysis program

    sort: sort=TRUE: sort items by the angle of the items on the first
          pair of factors.

_D_e_t_a_i_l_s:

     Although many uses of factor analysis/cluster analysis assume a
     simple structure where items have one and only one large loading,
     some domains such as personality or affect items have a more
     complex structure and some items have high loadings on two
     factors.  (These items are said to have complexity 2, see 'VSS'). 
     By expressing the factor loadings in polar coordinates, this
     structure is more readily perceived.

     For each pair of factors, item loadings are converted to an angle
     with the first factor, and a vector length corresponding to the
     amount of variance in the item shared with the two factors.  

     For a two dimensional structure, this will lead to a column of
     angles and a column of vector lengths.  For n factors, this leads
     to n* (n-1)/2 columns of angles and an equivalent number of vector
     lengths.

_V_a_l_u_e:

  polar : A data frame of polar coordinates 

_A_u_t_h_o_r(_s):

     William Revelle

_R_e_f_e_r_e_n_c_e_s:

     Rafaeli, E. & Revelle, W. (2006). A premature consensus: Are
     happiness and sadness truly opposite affects? Motivation and
     Emotion. \

     Hofstee, W. K. B., de Raad, B., & Goldberg, L. R. (1992).
     Integration of the big five and circumplex approaches to trait
     structure. Journal of Personality and Social Psychology, 63,
     146-163.

_S_e_e _A_l_s_o:

     'ICLUST', 'cluster.plot', 'circ.tests',  'factor.pa'

_E_x_a_m_p_l_e_s:

     circ.data <- circ.sim(24,500)
     circ.fa <- factor.pa(circ.data,2)
     circ.polar <- round(polar(circ.fa),2)
     circ.polar

