dressing          package:ffmanova          R Documentation(latin1)

_D_r_e_s_s_i_n_g _d_a_t_a

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

     A dataset from an experiment studying structural and rheological
     properties of a full fat dressing.

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

     data(dressing)

_F_o_r_m_a_t:

     A data frame with 29 observations on the following 7 variables.

     '_p_r_e_s_s' a numeric vector with values 75, 125 and 225. The
          homogenisation pressure.

     '_s_t_a_b' a numeric vector with values 0.3, 0.4 and 0.5. Amount of
          stabiliser.

     '_e_m_u_l' a numeric vector with values 0.1, 0.2 and 0.35. Amount of
          emulsifier.

     '_d_a_y' a factor with levels '1', ..., '5'. The day the experimental
          run was performed on.

     '_v_i_s_c' a numeric vector.  The measured viscosity of the dressing.

     '_r_h_e_o' a matrix with 9 columns.  Nine different
          response-parameters derived from rheological measuring. 
          These parameters contain information about the physics of the
          dression (more general that viscosity).

     '_p_v_o_l' a matrix with 241 columns.  Particle-volume curves.  Using
          a coulter-counter instrument fat particles were counted and
          their volumes were registered.  These data are presented as
          smoothed histograms (equally spaced bins on log-scale).  The
          total area under the curve represents the total volume of the
          counted fat particles. The shape of the curve reflects how
          the total fat volume is distributed among the different
          particle sizes.

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

     The data comes from an experiment in which full fat dressings were
     produced with different amount of stabiliser and emulsifier, and
     with different homogenisation pressure (se above).

     A full factorial 3^3 design with two additional center points was
     used.  The experiment was run over five days.  It was unknown up
     front how many experimental runs could be performed each day, so
     the order of the runs was randomised.

     For each dressing, viscosity, rheology and particle volume
     measurements were taken (se above).

     The day is stored as a factor.  The other design variables are
     stored as numerical variables.  If one wants to use them as
     factors, one can use e.g. 'factor(press)' in the model formula, or
     'dressing$press <- factor(dressing$press)' prior to calling the
     modelling function.

_S_o_u_r_c_e:

     The data is taken from a research project financed by a grant
     (131472/112) from the Norwegian Research Council.  The project was
     managed by Stabburet, which is a major manufacturer of dressing in
     Norway.

