diff --git a/main/coverage-report/index.html b/main/coverage-report/index.html index d2aaeec137..0d44a03ee3 100644 --- a/main/coverage-report/index.html +++ b/main/coverage-report/index.html @@ -94,7 +94,7 @@ font-size: 11px; }
-

tern coverage - 95.08%

+

tern coverage - 95.06%

-
- +
+
@@ -150635,21 +150635,21 @@

tern coverage - 95.08%

50 - 9x + 12x
  arm <- variables$arm
51 - 9x + 12x
  covariates <- variables$covariates
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  offset <- .df_row[[variables$offset]]
@@ -150663,14 +150663,14 @@

tern coverage - 95.08%

54 - 7x + 10x
  formula <- stats::as.formula(paste0(
55 - 7x + 10x
    .var, " ~ ",
@@ -150684,7 +150684,7 @@

tern coverage - 95.08%

57 - 7x + 10x
    paste(covariates, collapse = " + "),
@@ -150698,7 +150698,7 @@

tern coverage - 95.08%

59 - 7x + 10x
    arm
@@ -150719,35 +150719,35 @@

tern coverage - 95.08%

62 - 7x + 10x
  glm_fit <- stats::glm(
63 - 7x + 10x
    formula = formula,
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    offset = offset,
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    data = .df_row,
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    family = stats::poisson(link = "log")
@@ -150768,49 +150768,49 @@

tern coverage - 95.08%

69 - 7x + 10x
  emmeans_fit <- emmeans::emmeans(
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    glm_fit,
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    specs = arm,
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    data = .df_row,
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    type = "response",
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    offset = 0,
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    weights = weights
@@ -150831,21 +150831,21 @@

tern coverage - 95.08%

78 - 7x + 10x
  list(
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    glm_fit = glm_fit,
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    emmeans_fit = emmeans_fit
@@ -150964,21 +150964,21 @@

tern coverage - 95.08%

97 - 7x + 4x
  arm <- variables$arm
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  covariates <- variables$covariates
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  offset <- .df_row[[variables$offset]]
@@ -150992,14 +150992,14 @@

tern coverage - 95.08%

101 - 5x + 2x
  formula <- stats::as.formula(paste0(
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    .var, " ~ ",
@@ -151013,7 +151013,7 @@

tern coverage - 95.08%

104 - 5x + 2x
    paste(covariates, collapse = " + "),
@@ -151027,7 +151027,7 @@

tern coverage - 95.08%

106 - 5x + 2x
    arm
@@ -151048,35 +151048,35 @@

tern coverage - 95.08%

109 - 5x + 2x
  glm_fit <- stats::glm(
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    formula = formula,
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    offset = offset,
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    data = .df_row,
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    family = stats::quasipoisson(link = "log")
@@ -151097,49 +151097,49 @@

tern coverage - 95.08%

116 - 5x + 2x
  emmeans_fit <- emmeans::emmeans(
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    glm_fit,
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    specs = arm,
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    data = .df_row,
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    type = "response",
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    offset = 0,
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    weights = weights
@@ -151160,21 +151160,21 @@

tern coverage - 95.08%

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  list(
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    glm_fit = glm_fit,
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    emmeans_fit = emmeans_fit
@@ -151412,14 +151412,14 @@

tern coverage - 95.08%

161 - 6x + 9x
    poisson = h_glm_poisson(.var, .df_row, variables, weights),
- + 162 - 3x + !
    quasipoisson = h_glm_quasipoisson(.var, .df_row, variables, weights),
@@ -151552,14 +151552,14 @@

tern coverage - 95.08%

181 - 3x + 2x
  alpha <- 1 - conf_level
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  p <- 1 - alpha / 2
@@ -151573,7 +151573,7 @@

tern coverage - 95.08%

184 - 3x + 2x
  arm_levels <- levels(.df_row[[arm]])
@@ -151587,21 +151587,21 @@

tern coverage - 95.08%

186 - 3x + 2x
  out <- lapply(arm_levels, function(lev) {
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    temp <- .df_row
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    temp[[arm]] <- factor(lev, levels = arm_levels)
@@ -151615,14 +151615,14 @@

tern coverage - 95.08%

190 - 9x + 6x
    mf <- stats::model.frame(obj$formula, data = temp)
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    X <- stats::model.matrix(obj$formula, data = mf) # nolint
@@ -151636,14 +151636,14 @@

tern coverage - 95.08%

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    rate <- stats::predict(obj, newdata = mf, type = "response")
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    rate_hat <- mean(rate)
@@ -151657,28 +151657,28 @@

tern coverage - 95.08%

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    zz <- colMeans(rate * X)
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    se <- sqrt(as.numeric(t(zz) %*% stats::vcov(obj) %*% zz))
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    rate_lwr <- rate_hat * exp(-stats::qnorm(p) * se / rate_hat)
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    rate_upr <- rate_hat * exp(stats::qnorm(p) * se / rate_hat)
@@ -151692,7 +151692,7 @@

tern coverage - 95.08%

201 - 9x + 6x
    c(rate_hat, rate_lwr, rate_upr)
@@ -151713,21 +151713,21 @@

tern coverage - 95.08%

204 - 3x + 2x
  names(out) <- arm_levels
205 - 3x + 2x
  out <- do.call(rbind, out)
206 - 3x + 2x
  if ("negbin" %in% class(obj)) {
@@ -151748,7 +151748,7 @@

tern coverage - 95.08%

209 - 3x + 2x
    colnames(out) <- c("rate", "asymp.LCL", "asymp.UCL")
@@ -151762,21 +151762,21 @@

tern coverage - 95.08%

211 - 3x + 2x
  out <- as.data.frame(out)
212 - 3x + 2x
  out[[arm]] <- rownames(out)
213 - 3x + 2x
  out