ModelStatistics             package:cmm             R Documentation

_M_o_d_e_l_S_t_a_t_i_s_t_i_c_s

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

     If fitted frequencies under a model have been calculated, this
     procedure can be used to give sample values, fitted values,
     estimated standard errors, z-scores and adjusted residuals of one
     or more coefficients.

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

     ModelStatistics(dat, fitfreq, model, coeff, CoefficientDimensions="Automatic",
         Labels="Automatic",ShowCoefficients=TRUE,ShowParameters=FALSE,Method="ML", ParameterCoding="Effect", ShowCorrelations=FALSE, Title="")

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

     dat: observed data as a list of frequencies or as a data frame

 fitfreq: vector of fitted frequencies for each cell of full table
          (including latent variables, if any)

   model: list specified eg as 'list(bt,coeff,at)'

   coeff: list of coefficients, can be obtained using
          'SpecifyCoefficient'

CoefficientDimensions: numeric vector of dimensions of the table in
          which the coefficient vector is to be arranged

  Labels: list of characters or numbers indicating labels for
          dimensions of table in which the coefficient vector is to be
          arranged

ShowCoefficients: boolean, indicating whether or not the coefficients
          are to be displayed

ShowParameters: boolean, indicating whether or not the parameters
          (computed from the coefficients) are to be displayed

  Method: character, choice of "ML" for maximum likelihood or "GSK" for
          the GSK method

ParameterCoding: Coding to be used for parameters, choice of
          '"Effect"', '"Dummy"' and  '"Polynomial"'

ShowCorrelations: boolean, indicating whether or not to show the
          correlation matrix for the estimated coefficients

   Title: title of computation to appear at top of screen output

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

     The data can be a data frame or vector of frequencies.
     'MarginalModelFit' converts a data frame 'dat' using
     'c(t(ftable(dat)))'.

     For 'ParameterCoding', the default for '"Dummy"' is that the first
     cell in the table is the reference cell. Cell (i, j, k, ...) can
     be made reference cell using 'list("Dummy",c(i,j,k,...))'. For
     '"Polynomial"' the default is to use centralized scores based on
     equidistant (distance 1) linear scores, for example, if for
     i=1,2,3,4, mu_i = alpha + q_i beta + r_i gamma + s_i delta  where
     beta is a quadratic, gamma a cubic and delta a  quartic effect,
     then q_i takes the values (-1.5, -.5, .5, 1.5),  r_i takes the
     values (1, -1, -1, 1)  (centralized squares of the q_i), and s_i
     takes the values  (-3.375, -.125, .125, 3.375) (cubes of the q_i).

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

     NA. Only output to the screen is provided

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

     W. P. Bergsma w.p.bergsma@lse.ac.uk

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

     Bergsma, W. P. (1997). _Marginal models for categorical data_.
     Tilburg, The Netherlands: Tilburg University Press. <URL:
     http://stats.lse.ac.uk/bergsma/pdf/bergsma_phdthesis.pdf>

     Bergsma, W. P., Croon, M. A., & Hagenaars, J. A. P. (2009).
     Marginal models for dependent, clustered, and longitudunal
     categorical data. Berlin: Springer.

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

     'ModelStatistics', 'MarginalModelFit'

