epiTTest              package:epibasix              R Documentation

_E_p_i_d_e_m_i_o_l_o_g_i_c_a_l _T-_T_e_s_t _F_u_n_c_t_i_o_n

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

     This function computes the standard two sample T-Test, as well as
     performing hypothesis tests and computing confidence intervals for
     the equality of both population means.

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

     epiTTest(X,Y, alpha=0.05, pooled=FALSE, digits=3)

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

       X: A vector of observed values of a continuous random variable.

       Y: A vector of observed values of a continuous random variable.

   alpha: The desired Type I Error Rate for Confidence Intervals

  pooled: Logical: If TRUE, a pooled estimate of the variance is used. 
          That is, the variance is assumed to be equal in both groups. 
          If FALSE, the Satterthwaite estimate of the variance is used.

  digits: Number of Digits to round calculations

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

     This function performs the simple two-sample T-Test, while
     providing detailed information regarding the analysis and summary
     information for both groups.  Note that this function requires the
     input of two vectors, so if the data is stored in a matrix, it
     must be separated into two distinct vectors, X and Y.

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

      nx: The number of observations in X.

      ny: The number of observations in Y.

  mean.x: The sample mean of X.

  mean.y: The sample mean of Y.

     s.x: The standard deviation of X.

     s.y: The standard deviation of Y.

       d: The difference between sample means, that is, mean.x -
          mean.y.

     s2p: The pooled variance, when applicable.

      df: The degrees of freedom for the test.

   TStat: The test statistic for the null hypothesis mu_X - mu_Y = 0.

 p.value: The P-value for the test statistic for mu_X - mu_Y = 0.

     CIL: The lower bound of the constructed confidence interval for
          mu_X - mu_Y = 0.

     CIU: The lower bound of the constructed confidence interval for
          mu_X - mu_Y = 0.

  pooled: Logical: as above for assuming variances are equal.

   alpha: The desired Type I Error Rate for Confidence Intervals

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

     Michael Rotondi, mrotondi@uwo.ca

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

     Casella G and Berger RL.  Statistical Inference (2nd Ed.) Duxbury:
     New York, 2002.

     Szklo M and Nieto FJ.  Epidemiology: Beyond the Basics, Jones and
     Bartlett: Boston, 2007.

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

     X <- rnorm(100,10,1);
     Y <- rnorm(100);
     summary(epiTTest(X,Y, pooled = FALSE));

