nonadditivity           package:agricolae           R Documentation

_N_o_n_a_d_d_i_t_i_v_i_t_y _m_o_d_e_l _t_e_s_t

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

     The resistance for the transformable nonadditivity, due to J. W.
     Tukey,  is based on the detection of a curvilinear relation
     between y-est(y) and est(y). A freedom degree for the
     transformable nonadditivity.

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

     nonadditivity(y, factor1, factor2, df, MSerror)

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

       y: Answer of the experimental unit  

 factor1: Firts treatment applied to each experimental unit 

 factor2: Second treatment applied to each experimental unit 

      df: Degrees of freedom of the experimental error 

 MSerror: Means square error of the experimental 

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

     Only two factor: Block and treatment or factor 1 and factor 2.

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

      y : Numeric

factor1 : alfanumeric

factor2 : alfanumeric

     df : Numeric

MSerror : Numeric

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

     Felipe de Mendiburu

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

     1. Steel, R.; Torri,J; Dickey, D.(1997) Principles and Procedures
     of Statistics A Biometrical Approach

     2. George E.P. Box; J. Stuart Hunter and William G. Hunter. 
     Statistics for experimenters.  Wile Series in probability and
     statistics

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

     library(agricolae)
     data(potato )
     potato[,1]<-as.factor(potato[,1])
     model<-lm(cutting ~ date + variety,potato)
     df<-df.residual(model)
     MSerror<-deviance(model)/df
     attach(potato)
     analysis<-nonadditivity(cutting, date, variety, df, MSerror)
     detach(potato)

