n4props               package:epibasix               R Documentation

_N_u_m_b_e_r _o_f _S_u_b_j_e_c_t_s _R_e_q_u_i_r_e_d _f_o_r _a _R_a_n_d_o_m_i_z_e_d _T_r_i_a_l _w_i_t_h _B_i_n_a_r_y _O_u_t_c_o_m_e_s

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

     This function provides detailed sample size estimation information
     to determine the number of subjects that must be enrolled in a
     randomized trial with a binary outcome.

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

     n4props(pe, pc, alpha=0.05, power = 0.80, AR=1, two.tailed=TRUE, digits=3)

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

      pe: The anticipated proportion of individuals in the experimental
          group with the outcome.

      pc: The anticipated proportion of individuals in the control
          group with the outcome.

      AR: The Allocation Ratio: One implies an equal number of subjects
          per treatment and control group (maximum efficiency), > 1,
          implies more subjects will be enrolled in the control group 
          (e.g. in the case of costly intervention), < 1 implies more
          in the tretment group (rarely used).

   alpha: The desired Type I Error Rate

   power: The desired level of power, recall power = 1 - Type II Error.

two.tailed: Logical, If TRUE calculations are based on a two-tailed
          Type I error, if FALSE, a one-sided calculation is performed.

  digits: Number of Digits to round calculations

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

     This function provides detailed information, similar to PROC POWER
     in SAS, but with less functionality and more concise output.  It
     is used for sample size estimation in  a randomized trial where
     the response is binary.  A simple example may include whether an
     individual dies from a heart attack.  In epidemiological terms, pe
     and pc can be thought of as the expected prevalence of the outcome
     in the experimental and control group.

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

      nE: The minimum number of subjects required in the Experimental
          group.

      nC: The minimum number of subjects required in the Control group.

      pe: The anticipated proportion of individuals in the experimental
          group with the outcome.

      pc: The anticipated proportion of individuals in the control
          group with the outcome.

   alpha: The desired Type I Error Rate

   power: The desired level of power, recall power = 1 - Type II Error.

      AR: The Allocation Ratio

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

     Michael Rotondi, mrotondi@uwo.ca

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

     Matthews JNS.  Introduction to Randomized Controlled Clinical
     Trials (2nd Ed.) Chapman & Hall: New York, 2006.

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

     'n4means'

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

     ## Not run: Suppose a new drug is thought to reduce heart attack mortality from 0.10 to 0.03. Calculate the required number of subjects that must be enrolled in a study to detect this difference with alpha = 0.05 and power = 0.80.
     n4props(0.03, 0.10, AR=1, alpha=0.05, power=0.80);

