jinseob2kim
R/svyglm.R
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R/svycox.R
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R/glmshow.R
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Other files ignored by Codecov
DESCRIPTION
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NEWS.md
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Showing 6 of 8 files from the diff.
@@ -16,11 +16,11 @@
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| 16 | 16 | #' family = "gaussian", cor.type = "exchangeable") |
|
| 17 | 17 | #' @rdname geeUni |
|
| 18 | 18 | #' @importFrom geepack geeglm |
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| 19 | - | #' @importFrom stats as.formula |
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| 19 | + | #' @importFrom stats as.formula update |
|
| 20 | 20 | #' @export |
|
| 21 | 21 | ||
| 22 | 22 | ||
| 23 | - | geeUni = function(y, x, data, id.vec, family, cor.type = "exchangeable"){ |
|
| 23 | + | geeUni <- function(y, x, data, id.vec, family, cor.type = "exchangeable"){ |
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| 24 | 24 | form <- as.formula(paste(y, "~", x)) |
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| 25 | 25 | res <- geepack::geeglm(form, data = data, family = family, id = id.vec, corstr = cor.type) |
|
| 26 | 26 | coef <- summary(res)$coefficients[-1, -3] |
@@ -47,7 +47,7 @@
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| 47 | 47 | #' @export |
|
| 48 | 48 | ||
| 49 | 49 | ||
| 50 | - | geeExp = function(gee.coef, family ="binomial", dec){ |
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| 50 | + | geeExp <- function(gee.coef, family ="binomial", dec){ |
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| 51 | 51 | if (family == "binomial"){ |
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| 52 | 52 | OR <- paste(round(exp(gee.coef[,1]), dec), " (", round(exp(gee.coef[,1] - 1.96*gee.coef[,2]), dec), ",", round(exp(gee.coef[,1] + 1.96*gee.coef[,2]), dec),")", sep="") |
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| 53 | 53 | return(cbind(OR, gee.coef[,3])) |
@@ -81,17 +81,19 @@
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| 81 | 81 | #' @rdname geeglm.display |
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| 82 | 82 | #' @export |
|
| 83 | 83 | #' @importFrom data.table data.table |
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| 84 | - | #' @importFrom stats complete.cases |
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| 84 | + | #' @importFrom stats complete.cases update formula |
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| 85 | 85 | ||
| 86 | - | geeglm.display = function(geeglm.obj, decimal = 2){ |
|
| 86 | + | geeglm.display <- function(geeglm.obj, decimal = 2){ |
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| 87 | 87 | family.gee <- geeglm.obj$family[[1]] |
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| 88 | 88 | corstr.gee <- geeglm.obj$corstr |
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| 89 | 89 | y <- as.character(geeglm.obj$terms[[2]]) |
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| 90 | 90 | xs <- names(geeglm.obj$model)[-1] |
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| 91 | 91 | ## rownames |
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| 92 | 92 | geeglm.obj$data <- data.table::data.table(geeglm.obj$data) |
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| 93 | - | nomiss <- stats::complete.cases(geeglm.obj$data[, c(y, xs), with = F]) |
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| 94 | - | gee.uni.list <- lapply(xs, function(x){geeUni(y, x, data = geeglm.obj$data[nomiss, ], id.vec = geeglm.obj$id, family = family.gee, cor.type = corstr.gee)}) |
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| 93 | + | #nomiss <- stats::complete.cases(geeglm.obj$data[, c(y, xs), with = F]) |
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| 94 | + | basemodel <- stats::update(geeglm.obj, stats::formula(paste(c(". ~ .", xs), collapse=' - ')), data = geeglm.obj$data) |
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| 95 | + | #gee.uni.list <- lapply(xs, function(x){geeUni(y, x, data = geeglm.obj$data[nomiss, ], id.vec = geeglm.obj$id, family = family.gee, cor.type = corstr.gee)}) |
|
| 96 | + | gee.uni.list <- lapply(xs, function(x){summary(stats::update(basemodel, stats::formula(paste0(". ~ . +", x)), data = geeglm.obj$data))$coefficients[-1, -3]}) |
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| 95 | 97 | rn.uni <- lapply(gee.uni.list, rownames) |
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| 96 | 98 | gee.uni <- Reduce(rbind, gee.uni.list) |
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| 97 | 99 |
@@ -16,6 +16,7 @@
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| 16 | 16 | #' @rdname svyglm.display |
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| 17 | 17 | #' @export |
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| 18 | 18 | #' @importFrom survey svyglm |
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| 19 | + | #' @importFrom stats update |
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| 19 | 20 | ||
| 20 | 21 | ||
| 21 | 22 | svyregress.display <- function(svyglm.obj, decimal = 2){ |
@@ -29,7 +30,7 @@
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| 29 | 30 | if (length(xs) == 0){ |
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| 30 | 31 | stop("No independent variable") |
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| 31 | 32 | } else if (length(xs) ==1){ |
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| 32 | - | uni <- data.frame(coefNA(survey::svyglm(as.formula(paste(y, " ~ ", xs)), design = design.model, family = model$family)))[-1, ] |
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| 33 | + | uni <- data.frame(coefNA(model))[-1, ] |
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| 33 | 34 | rn.uni <- lapply(list(uni), rownames) |
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| 34 | 35 | #uni <- data.frame(summary(survey::svyglm(as.formula(paste(y, " ~ ", xs)), design = design.model, family = model$family))$coefficients)[-1, ] |
|
| 35 | 36 | if (gaussianT){ |
@@ -46,7 +47,7 @@
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| 46 | 47 | ||
| 47 | 48 | } else{ |
|
| 48 | 49 | uni <- lapply(xs, function(v){ |
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| 49 | - | data.frame(coefNA(survey::svyglm(as.formula(paste(y, " ~ ", v)), design = design.model, family = model$family)))[-1, ] |
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| 50 | + | data.frame(coefNA(stats::update(model, formula(paste(paste(c(". ~ .", xs), collapse=' - '), " + ", v)), design = design.model)))[-1, ] |
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| 50 | 51 | }) |
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| 51 | 52 | #uni <- lapply(xs, function(v){ |
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| 52 | 53 | # summary(survey::svyglm(as.formula(paste(y, " ~ ", v)), design = design.model))$coefficients[-1, ] |
@@ -11,19 +11,19 @@
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| 11 | 11 | #' @importFrom stats pnorm |
|
| 12 | 12 | ||
| 13 | 13 | ||
| 14 | - | lmerExp = function(lmer.coef, family ="binomial", dec){ |
|
| 14 | + | lmerExp <- function(lmer.coef, family ="binomial", dec){ |
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| 15 | 15 | if (class(lmer.coef)[1] == "numeric"){ |
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| 16 | - | lmer.coef = t(data.frame(lmer.coef)) |
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| 16 | + | lmer.coef <- t(data.frame(lmer.coef)) |
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| 17 | 17 | } |
|
| 18 | - | pv = 2*(1-pnorm(abs(lmer.coef[,3]))) |
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| 18 | + | pv <- 2*(1-pnorm(abs(lmer.coef[,3]))) |
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| 19 | 19 | if (family == "binomial"){ |
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| 20 | - | OR = paste(round(exp(lmer.coef[,1]), dec), " (", round(exp(lmer.coef[,1] - 1.96*lmer.coef[,2]), dec), ",", round(exp(lmer.coef[,1] + 1.96*lmer.coef[,2]), dec),")", sep="") |
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| 20 | + | OR <- paste(round(exp(lmer.coef[,1]), dec), " (", round(exp(lmer.coef[,1] - 1.96*lmer.coef[,2]), dec), ",", round(exp(lmer.coef[,1] + 1.96*lmer.coef[,2]), dec),")", sep="") |
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| 21 | 21 | return(cbind(OR, pv)) |
|
| 22 | 22 | } else if (family %in% c(NULL, "gaussian")){ |
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| 23 | - | coeff = paste(round(lmer.coef[,1], dec), " (", round(lmer.coef[,1] - 1.96*lmer.coef[,2], dec), ",", round(lmer.coef[,1] + 1.96*lmer.coef[,2], dec), ")", sep="") |
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| 23 | + | coeff <- paste(round(lmer.coef[,1], dec), " (", round(lmer.coef[,1] - 1.96*lmer.coef[,2], dec), ",", round(lmer.coef[,1] + 1.96*lmer.coef[,2], dec), ")", sep="") |
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| 24 | 24 | return(cbind(coeff, pv)) |
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| 25 | 25 | } else if (family %in% c("poisson", "quasipoisson")){ |
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| 26 | - | RR = paste(round(exp(lmer.coef[,1]), dec), " (", round(exp(lmer.coef[,1] - 1.96*lmer.coef[,2]), dec), ",", round(exp(lmer.coef[,1] + 1.96*lmer.coef[,2]), dec),")", sep="") |
|
| 26 | + | RR <- paste(round(exp(lmer.coef[,1]), dec), " (", round(exp(lmer.coef[,1] - 1.96*lmer.coef[,2]), dec), ",", round(exp(lmer.coef[,1] + 1.96*lmer.coef[,2]), dec),")", sep="") |
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| 27 | 27 | return(cbind(RR, pv)) |
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| 28 | 28 | } |
|
| 29 | 29 | } |
@@ -50,87 +50,84 @@
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| 50 | 50 | #' @rdname lmer.display |
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| 51 | 51 | #' @export |
|
| 52 | 52 | #' @importFrom lme4 lmer glmer confint.merMod |
|
| 53 | + | #' @importFrom stats update formula |
|
| 53 | 54 | ||
| 54 | - | lmer.display = function(lmerMod.obj, dec = 2, ci.ranef = F){ |
|
| 55 | - | sl = summary(lmerMod.obj) |
|
| 56 | - | fixef = sl$coefficients[-1,] |
|
| 55 | + | lmer.display <- function(lmerMod.obj, dec = 2, ci.ranef = F){ |
|
| 56 | + | sl <- summary(lmerMod.obj) |
|
| 57 | + | fixef <- sl$coefficients[-1,] |
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| 57 | 58 | ||
| 58 | - | mdata = lmerMod.obj@frame |
|
| 59 | - | forms = as.character(sl$call[[2]]) |
|
| 60 | - | y = forms[2] |
|
| 61 | - | xfr = strsplit(forms[3]," \\+ ")[[1]] |
|
| 62 | - | xr = xfr[grepl("\\|", xfr)] |
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| 63 | - | xf = xfr[!grepl("\\|", xfr)] |
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| 64 | - | family.lmer = ifelse(is.null(sl$family), "gaussian", sl$family) |
|
| 65 | - | uni.res = "" |
|
| 66 | - | if (family.lmer == "gaussian"){ |
|
| 67 | - | unis = lapply(xf, function(x){summary(lmer(as.formula(paste(y, "~", x," + ", paste(xr, collapse =" + "), sep="")), data = mdata))$coefficients}) |
|
| 68 | - | unis2 = Reduce(rbind, unis) |
|
| 69 | - | uni.res <- unis2[rownames(unis2) != "(Intercept)",] |
|
| 70 | - | } else{ |
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| 71 | - | unis = lapply(xf, function(x){summary(glmer(as.formula(paste(y, "~", x," + ", paste(xr, collapse =" + "), sep="")), data = mdata, family = family.lmer))$coefficients}) |
|
| 72 | - | unis2 = Reduce(rbind, unis) |
|
| 73 | - | uni.res <- unis2[rownames(unis2) != "(Intercept)",] |
|
| 74 | - | } |
|
| 59 | + | mdata <- lmerMod.obj@frame |
|
| 60 | + | forms <- as.character(sl$call[[2]]) |
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| 61 | + | y <- forms[2] |
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| 62 | + | xfr <- strsplit(forms[3]," \\+ ")[[1]] |
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| 63 | + | xr <- xfr[grepl("\\|", xfr)] |
|
| 64 | + | xf <- xfr[!grepl("\\|", xfr)] |
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| 65 | + | family.lmer <- ifelse(is.null(sl$family), "gaussian", sl$family) |
|
| 66 | + | uni.res <- "" |
|
| 67 | + | basemodel <- update(lmerMod.obj, stats::formula(paste(c(". ~ .", xf), collapse=' - ')), data = mdata) |
|
| 68 | + | unis <- lapply(xf, function(x){summary(stats::update(basemodel, stats::formula(paste0(". ~ . +", x)), data = mdata))$coefficients}) |
|
| 69 | + | unis2 <- Reduce(rbind, unis) |
|
| 70 | + | uni.res <- unis2[rownames(unis2) != "(Intercept)",] |
|
| 71 | + | ||
| 75 | 72 | ||
| 76 | 73 | if(length(xf) == 1){ |
|
| 77 | - | fix.all = lmerExp(uni.res, family=family.lmer, dec = dec) |
|
| 78 | - | family.label = colnames(fix.all)[1] |
|
| 79 | - | colnames(fix.all) = c(paste(family.label, "(95%CI)",sep = ""), "P value") |
|
| 80 | - | rownames(fix.all) = rownames(sl$coefficients)[-1] |
|
| 74 | + | fix.all <- lmerExp(uni.res, family=family.lmer, dec = dec) |
|
| 75 | + | family.label <- colnames(fix.all)[1] |
|
| 76 | + | colnames(fix.all) <- c(paste(family.label, "(95%CI)",sep = ""), "P value") |
|
| 77 | + | rownames(fix.all) <- rownames(sl$coefficients)[-1] |
|
| 81 | 78 | } else{ |
|
| 82 | - | fix.all = cbind(lmerExp(uni.res, family=family.lmer, dec = dec), lmerExp(fixef, family=family.lmer, dec = dec)) |
|
| 83 | - | family.label = colnames(fix.all)[1] |
|
| 84 | - | colnames(fix.all) = c(paste("crude ", family.label, "(95%CI)",sep = ""), "crude P value", paste("adj. ", family.label, "(95%CI)",sep = ""), "adj. P value") |
|
| 85 | - | rownames(fix.all) = rownames(sl$coefficients)[-1] |
|
| 79 | + | fix.all <- cbind(lmerExp(uni.res, family=family.lmer, dec = dec), lmerExp(fixef, family=family.lmer, dec = dec)) |
|
| 80 | + | family.label <- colnames(fix.all)[1] |
|
| 81 | + | colnames(fix.all) <- c(paste("crude ", family.label, "(95%CI)",sep = ""), "crude P value", paste("adj. ", family.label, "(95%CI)",sep = ""), "adj. P value") |
|
| 82 | + | rownames(fix.all) <- rownames(sl$coefficients)[-1] |
|
| 86 | 83 | } |
|
| 87 | 84 | ||
| 88 | - | ranef = data.frame(sl$varcor)[,c(1,4)] |
|
| 89 | - | ranef.out = cbind(as.character(round(ranef[,2], dec)), matrix(NA, nrow(ranef), ncol(fix.all) - 1 )) |
|
| 90 | - | rownames(ranef.out) = ranef[,1] |
|
| 85 | + | ranef <- data.frame(sl$varcor)[,c(1,4)] |
|
| 86 | + | ranef.out <- cbind(as.character(round(ranef[,2], dec)), matrix(NA, nrow(ranef), ncol(fix.all) - 1 )) |
|
| 87 | + | rownames(ranef.out) <- ranef[,1] |
|
| 91 | 88 | if (ci.ranef){ |
|
| 92 | - | ranef.ci = confint.merMod(lmerMod.obj, parm = 1:nrow(ranef), oldNames = F)^2 |
|
| 93 | - | ranef.paste = paste(round(ranef$vcov, dec)," (", round(ranef.ci[,1], dec), ",", round(ranef.ci[,2], dec),")", sep="") |
|
| 94 | - | ranef.out = cbind(ranef.paste, matrix(NA, nrow(ranef), 3)) |
|
| 95 | - | rownames(ranef.out) = ranef[,1] |
|
| 89 | + | ranef.ci <- confint.merMod(lmerMod.obj, parm = 1:nrow(ranef), oldNames = F)^2 |
|
| 90 | + | ranef.paste <- paste(round(ranef$vcov, dec)," (", round(ranef.ci[,1], dec), ",", round(ranef.ci[,2], dec),")", sep="") |
|
| 91 | + | ranef.out <- cbind(ranef.paste, matrix(NA, nrow(ranef), 3)) |
|
| 92 | + | rownames(ranef.out) <- ranef[,1] |
|
| 96 | 93 | } |
|
| 97 | 94 | ||
| 98 | - | ranef.na = rbind(rep(NA, ncol(fix.all)), ranef.out) |
|
| 99 | - | rownames(ranef.na)[1] = "Random effects" |
|
| 100 | - | colnames(ranef.na) = colnames(fix.all) |
|
| 95 | + | ranef.na <- rbind(rep(NA, ncol(fix.all)), ranef.out) |
|
| 96 | + | rownames(ranef.na)[1] <- "Random effects" |
|
| 97 | + | colnames(ranef.na) <- colnames(fix.all) |
|
| 101 | 98 | ||
| 102 | 99 | ||
| 103 | 100 | ## rownames |
|
| 104 | - | fix.all.list = lapply(xf, function(x){fix.all[grepl(x, rownames(fix.all)),]}) |
|
| 105 | - | varnum.mfac = which(lapply(fix.all.list, length) > ncol(fix.all)) |
|
| 101 | + | fix.all.list <- lapply(xf, function(x){fix.all[grepl(x, rownames(fix.all)),]}) |
|
| 102 | + | varnum.mfac <- which(lapply(fix.all.list, length) > ncol(fix.all)) |
|
| 106 | 103 | lapply(varnum.mfac, function(x){fix.all.list[[x]] <<- rbind(rep(NA, ncol(fix.all)), fix.all.list[[x]])}) |
|
| 107 | - | fix.all.unlist = Reduce(rbind, fix.all.list) |
|
| 104 | + | fix.all.unlist <- Reduce(rbind, fix.all.list) |
|
| 108 | 105 | ||
| 109 | - | rn.list = lapply(xf, function(x){rownames(fix.all)[grepl(x, rownames(fix.all))]}) |
|
| 110 | - | varnum.2fac = which(lapply(xf, function(x){length(sapply(mdata, levels)[[x]])}) == 2) |
|
| 106 | + | rn.list <- lapply(xf, function(x){rownames(fix.all)[grepl(x, rownames(fix.all))]}) |
|
| 107 | + | varnum.2fac <- which(lapply(xf, function(x){length(sapply(mdata, levels)[[x]])}) == 2) |
|
| 111 | 108 | lapply(varnum.2fac, function(x){rn.list[[x]] <<- paste(xf[x], ": ", levels(mdata[, xf[x]])[2], " vs ", levels(mdata[, xf[x]])[1], sep="")}) |
|
| 112 | 109 | lapply(varnum.mfac, function(x){rn.list[[x]] <<- c(paste(xf[x],": ref.=", levels(mdata[, xf[x]])[1], sep=""), gsub(xf[x]," ", rn.list[[x]]))}) |
|
| 113 | 110 | if (class(fix.all.unlist)[1] == "character"){ |
|
| 114 | - | fix.all.unlist = t(data.frame(fix.all.unlist)) |
|
| 111 | + | fix.all.unlist <- t(data.frame(fix.all.unlist)) |
|
| 115 | 112 | } |
|
| 116 | - | rownames(fix.all.unlist) = unlist(rn.list) |
|
| 117 | - | tb.df = as.data.frame(rbind(fix.all.unlist, ranef.na)) |
|
| 113 | + | rownames(fix.all.unlist) <- unlist(rn.list) |
|
| 114 | + | tb.df <- as.data.frame(rbind(fix.all.unlist, ranef.na)) |
|
| 118 | 115 | ||
| 119 | 116 | ||
| 120 | 117 | ## metric |
|
| 121 | - | no.grp = sl$ngrps |
|
| 122 | - | no.obs = nrow(mdata) |
|
| 123 | - | ll = round(sl$logLik[[1]], dec) |
|
| 124 | - | aic = round(sl$AICtab, dec)[1] |
|
| 125 | - | met = c(NA, no.grp, no.obs, ll, aic) |
|
| 126 | - | met.mat = cbind(met, matrix(NA, length(met), ncol(fix.all) - 1 )) |
|
| 127 | - | rownames(met.mat) = c("Metrics", paste("No. of groups (", rownames(met.mat)[2:(length(no.grp) + 1)], ")", sep=""), "No. of observations", "Log-likelihood", "AIC value") |
|
| 128 | - | met.mat[, 1] = as.character(met.mat[, 1]) |
|
| 129 | - | colnames(met.mat) = colnames(tb.df) |
|
| 130 | - | tb.lmerMod = rbind(tb.df, met.mat) |
|
| 118 | + | no.grp <- sl$ngrps |
|
| 119 | + | no.obs <- nrow(mdata) |
|
| 120 | + | ll <- round(sl$logLik[[1]], dec) |
|
| 121 | + | aic <- round(sl$AICtab, dec)[1] |
|
| 122 | + | met <- c(NA, no.grp, no.obs, ll, aic) |
|
| 123 | + | met.mat <- cbind(met, matrix(NA, length(met), ncol(fix.all) - 1 )) |
|
| 124 | + | rownames(met.mat) <- c("Metrics", paste("No. of groups (", rownames(met.mat)[2:(length(no.grp) + 1)], ")", sep=""), "No. of observations", "Log-likelihood", "AIC value") |
|
| 125 | + | met.mat[, 1] <- as.character(met.mat[, 1]) |
|
| 126 | + | colnames(met.mat) <- colnames(tb.df) |
|
| 127 | + | tb.lmerMod <- rbind(tb.df, met.mat) |
|
| 131 | 128 | lapply(seq(2, ncol(fix.all), by =2), function(x){tb.lmerMod[, x] <<- as.numeric(as.vector(tb.lmerMod[, x]))}) |
|
| 132 | 129 | ||
| 133 | 130 | ## caption |
|
| 134 | - | cap.lmerMod = paste(sl$methTitle, " : ", y," ~ ", forms[3], sep="") |
|
| 131 | + | cap.lmerMod <- paste(sl$methTitle, " : ", y," ~ ", forms[3], sep="") |
|
| 135 | 132 | return(list(table = tb.lmerMod, caption = cap.lmerMod)) |
|
| 136 | 133 | } |
@@ -25,7 +25,7 @@
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| 25 | 25 | #' @rdname svycox.display |
|
| 26 | 26 | #' @export |
|
| 27 | 27 | #' @importFrom survey svycoxph |
|
| 28 | - | #' @importFrom stats AIC |
|
| 28 | + | #' @importFrom stats AIC update |
|
| 29 | 29 | ||
| 30 | 30 | ||
| 31 | 31 | svycox.display <- function(svycoxph.obj, decimal = 2){ |
@@ -48,10 +48,10 @@
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| 48 | 48 | rownames(fix.all) <- names(model$coefficients) |
|
| 49 | 49 | } else { |
|
| 50 | 50 | unis <- lapply(xf, function(x){ |
|
| 51 | - | uni.res <- data.frame(summary(survey::svycoxph(as.formula(paste(formula.surv, "~", x, sep="")), design = design.model))$coefficients) |
|
| 52 | - | names(uni.res)[ncol(uni.res)] <- "p" |
|
| 53 | - | uni.res2 <- uni.res[, c("coef", grep("se", colnames(uni.res), value = T)[length(grep("se", colnames(uni.res)))], "z", "p")] |
|
| 54 | - | return(uni.res2) |
|
| 51 | + | uni.res <- data.frame(summary(stats::update(model, formula(paste(paste(c(". ~ .", xf), collapse=' - '), " + ", x)), design = design.model))$coefficients) |
|
| 52 | + | names(uni.res)[ncol(uni.res)] <- "p" |
|
| 53 | + | uni.res2 <- uni.res[, c("coef", grep("se", colnames(uni.res), value = T)[length(grep("se", colnames(uni.res)))], "z", "p")] |
|
| 54 | + | return(uni.res2) |
|
| 55 | 55 | }) |
|
| 56 | 56 | ||
| 57 | 57 | unis2 <- Reduce(rbind, unis) |
@@ -89,9 +89,9 @@
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| 89 | 89 | if (!is.null(xc.vn)){ |
|
| 90 | 90 | names(mdata2)[ncol(mdata2)] <- xc.vn |
|
| 91 | 91 | } |
|
| 92 | - | basemodel <- update(model, formula(paste(c(". ~ .", xf), collapse=' - ')), data = mdata2) |
|
| 92 | + | basemodel <- update(model, stats::formula(paste(c(". ~ .", xf), collapse=' - ')), data = mdata2) |
|
| 93 | 93 | unis <- lapply(xf, function(x){ |
|
| 94 | - | newfit <- update(basemodel, formula(paste0(". ~ . +", x)), data= mdata2) |
|
| 94 | + | newfit <- update(basemodel, stats::formula(paste0(". ~ . +", x)), data= mdata2) |
|
| 95 | 95 | uni.res <- data.frame(summary(newfit)$coefficients) |
|
| 96 | 96 | uni.res <- uni.res[grep(x, rownames(uni.res)), ] |
|
| 97 | 97 | #uni.res <- uni.res[c(2:nrow(uni.res), 1), ] |
@@ -30,7 +30,7 @@
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| 30 | 30 | #' \code{\link[stats]{glm}} |
|
| 31 | 31 | #' @rdname glmshow.display |
|
| 32 | 32 | #' @export |
|
| 33 | - | #' @importFrom stats glm cor predict |
|
| 33 | + | #' @importFrom stats glm cor predict formula |
|
| 34 | 34 | ||
| 35 | 35 | glmshow.display <- function (glm.object, decimal = 2){ |
|
| 36 | 36 | model <- glm.object |
@@ -45,7 +45,7 @@
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| 45 | 45 | if (length(xs) == 0){ |
|
| 46 | 46 | stop("No independent variable") |
|
| 47 | 47 | } else if (length(xs) ==1){ |
|
| 48 | - | uni <- data.frame(coefNA(stats::glm(as.formula(paste(y, " ~ ", xs)), data = data, family = model$family)))[-1, ] |
|
| 48 | + | uni <- data.frame(coefNA(glm.object))[-1, ] |
|
| 49 | 49 | rn.uni <- lapply(list(uni), rownames) |
|
| 50 | 50 | if (gaussianT){ |
|
| 51 | 51 | summ <- paste(round(uni[,1], decimal), " (", round(uni[, 1] - 1.96*uni[, 2], decimal), "," ,round(uni[, 1] + 1.96*uni[, 2], decimal), ")", sep ="") |
@@ -60,8 +60,11 @@
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| 60 | 60 | res <- uni.res |
|
| 61 | 61 | ||
| 62 | 62 | } else{ |
|
| 63 | + | basemodel <- stats::update(model, formula(paste(c(". ~ .", xs), collapse=' - ')), data = data) |
|
| 64 | + | ||
| 63 | 65 | uni <- lapply(xs, function(v){ |
|
| 64 | - | data.frame(coefNA(stats::glm(as.formula(paste(y, " ~ ", v)), data = data, family = model$family)))[-1, ] |
|
| 66 | + | data.frame(coefNA(stats::update(basemodel, formula(paste0(". ~ . +", v)), data = data))) |
|
| 67 | + | #data.frame(coefNA(stats::glm(as.formula(paste(y, " ~ ", v)), data = data, family = model$family)))[-1, ] |
|
| 65 | 68 | }) |
|
| 66 | 69 | rn.uni <- lapply(uni, rownames) |
|
| 67 | 70 | uni <- Reduce(rbind, uni) |
| Files | Coverage |
|---|---|
| R | 84.82% |
| Project Totals (13 files) | 84.82% |
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Sunburst
The inner-most circle is the entire project, moving away from the center are folders then, finally, a single file.
The size and color of each slice is representing the number of statements and the coverage, respectively.
Icicle
The top section represents the entire project. Proceeding with folders and finally individual files.
The size and color of each slice is representing the number of statements and the coverage, respectively.
