~~function to do ... ~~

Description

~~ A concise (1-5 lines) description of what the function does. ~~

Usage

m2regress(X, Y, type = "RMA", zero = F)

Arguments

Details

~~ If necessary, more details than the description above ~~

Value

~Describe the value returned If it is a LIST, use

comp1	Description of 'comp1'
comp2	Description of 'comp2'

...

Note

~~further notes~~

~Make other sections like Warning with Warning .... ~

Author(s)

~~who you are~~

References

~put references to the literature/web site here ~

See Also

~~objects to See Also as help, ~~~

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (X, Y, type = "RMA", zero = F) 
{
    IV <- X
    DV <- Y
    ssx <- sum((IV - mean(IV))^2)
    ssy <- sum((DV - mean(DV))^2)
    sxy <- sum(((IV - mean(IV))) * ((DV - mean(DV))))
    r <- sxy/sqrt(ssx * ssy)
    r2 <- sxy/(ssx * ssy)
    df.DV <- length(DV) - 2
    n <- length(IV)
    s2xy <- abs((ssy - (sxy^2)/ssx)/(length(IV) - 2))
    mod <- lm(DV ~ IV)
    if (type == "OLS") {
        b <- sxy/ssx
        a <- mean(DV) - b * mean(IV)
        pp <- length(IV)
        sb <- sqrt((s2xy/ssx))
        sa <- sqrt(s2xy * (1/(length(IV) - 0) + (mean(IV)^2)/ssx))
        ci <- qt(0.975, length(IV) - 2) * sb
        bLower <- b - ci
        bUpper <- b + ci
        aCI <- qt(0.975, length(IV) - 2) * sa
        aLower <- a - aCI
        aUpper <- a + aCI
    }
    if (type == "MA") {
        b_ols <- sxy/ssx
        r2 <- (sxy/sqrt(ssx * ssy))^2
        d <- (b_ols^2 - r2)/(r2 * b_ols)
        b <- (d + sqrt(d^2 + 4))/2
        a <- mean(DV) - b * mean(IV)
        sb <- sqrt((s2xy/ssx))
        sa <- sqrt(s2xy * (1/(length(IV) - 0) + (mean(IV)^2)/ssx))
        B <- ((qt(0.975, n - 2)^2)) * ((1 - r2))/(n - 2)
        bUpper <- b * (sqrt(B + 1) + sqrt(B))
        bLower <- b * (sqrt(B + 1) - sqrt(B))
        aLower <- mean(DV) - (bUpper * mean(IV))
        aUpper <- mean(DV) - (bLower * mean(IV))
    }
    if (type == "rMA") {
        if (zero == F) {
            rIV <- (X - min(X))/(max(X) - min(X))
            rDV <- (Y - min(Y))/(max(Y) - min(Y))
        }
        if (zero == T) {
            rIV <- (X)/(max(X))
            rDV <- (Y)/(max(Y))
        }
        rssx <- sum((rIV - mean(rIV))^2)
        rssy <- sum((rDV - mean(rDV))^2)
        rsxy <- sum(((rIV - mean(rIV))) * ((rDV - mean(rDV))))
        rr <- rsxy/sqrt(rssx * rssy)
        rr2 <- rr^2
        rb_ols <- rsxy/rssx
        d <- (rb_ols^2 - rr2)/(rr2 * rb_ols)
        b <- (d + sqrt(d^2 + 4))/2
        rn <- length(rIV)
        rs2xy <- abs((rssy - (rsxy^2)/rssx)/(length(rIV) - 2))
        if (zero == F) 
            b <- b * ((max(Y) - min(Y))/(max(X) - min(X)))
        if (zero == T) 
            b <- b * ((max(Y))/(max(X)))
        a <- mean(DV) - b * mean(IV)
        sb <- sqrt((rs2xy/rssx))
        sa <- sqrt(rs2xy * (1/(length(rIV) - 0) + (mean(rIV)^2)/rssx))
        B <- ((qt(0.975, rn - 2)^2)) * ((1 - rr2))/(n - 2)
        bUpper <- b * (sqrt(B + 1) + sqrt(B))
        bLower <- b * (sqrt(B + 1) - sqrt(B))
        aLower <- mean(DV) - (bUpper * mean(IV))
        aUpper <- mean(DV) - (bLower * mean(IV))
    }
    if (type == "RMA") {
        r2 <- (sxy/sqrt(ssx * ssy))^2
        b <- sqrt(ssy/ssx)
        if (sxy < 0) 
            b <- b * -1
        a <- mean(DV) - (b * mean(IV))
        sb <- sqrt((s2xy/ssx))
        sa <- sqrt(s2xy * (1/(length(IV) - 0) + (mean(IV)^2)/ssx))
        n <- length(IV)
        ci <- qt(0.975, length(IV) - 2) * sb
        bLower <- b - ci
        bUpper <- b + ci
        B <- ((qt(0.975, n - 2)^2)) * ((1 - r2))/(n - 2)
        bUpper <- b * (sqrt(B + 1) + sqrt(B))
        bLower <- b * (sqrt(B + 1) - sqrt(B))
        aCI <- qt(0.975, length(IV) - 2) * sa
        aLower <- a - aCI
        aUpper <- a + aCI
        aLower <- mean(DV) - (bUpper * mean(IV))
        aUpper <- mean(DV) - (bLower * mean(IV))
    }
    coef <- matrix(NA, 2, 1, dimnames = list(c("(Intercept)", 
        "X"), c("Coef")))
    stats <- matrix(NA, 2, 5, dimnames = list(c("(Intercept)", 
        "X"), c("SE", "t", "P|>t|", "2.5", "97.5")))
    coef[1, 1] <- a
    coef[2, 1] <- b
    stats[1, 1] <- sa
    stats[2, 1] <- sb
    stats[1, 2] <- a/sa
    stats[2, 2] <- b/sb
    stats[1, 3] <- 2 * pt(abs(abs(a/sa)), length(DV) - 2, lower.tail = F)
    stats[2, 3] <- 2 * pt(abs(b/sb), length(DV) - 2, lower.tail = F)
    stats[1, 4] <- aLower
    stats[1, 5] <- aUpper
    stats[2, 4] <- bLower
    stats[2, 5] <- bUpper
    z <- list(coefficients = coef, stats = stats)
    z
  }