# Fit models of different type
res1 <-
expirest_wisle(data = exp1[exp1$Batch %in% c("b2", "b5", "b7"), ],
response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", rl = 98, rl_sf = 3, sl = 95,
sl_sf = 3, srch_range = c(0, 500), sf_option = "loose")
res2 <-
expirest_wisle(data = exp1[exp1$Batch %in% c("b3", "b4", "b5"), ],
response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", rl = 98, rl_sf = 3, sl = 95,
sl_sf = 3, srch_range = c(0, 500), sf_option = "loose")
res3 <-
expirest_wisle(data = exp1[exp1$Batch %in% c("b4", "b5", "b8"), ],
response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", rl = 98, rl_sf = 3, sl = 95,
sl_sf = 3, srch_range = c(0, 500), sf_option = "loose")
# The parameter settings sf_option = "loose" and ivl_side = "lower" (the
# default setting of ivl_side) cause the specification limit of 95.0
# (sl_sf = 3, i.e. 3 significant digits) to be reduced by 0.05, i.e. the
# actual specification limit is 94.95.
if (FALSE) {
res1
# Expected output of print(res1)
# Summary of shelf life estimation following the ARGPM
# guidance "Stability testing for prescription medicines"
#
# The best model accepted at a significance level of 0.25 has
# Common intercepts and Common slopes (acronym: cics).
#
# Worst case intercept and batch:
# RL Batch Intercept
# 1 98 NA 100.5669
#
# Estimated shelf lives for the cics model:
# SL RL wisle osle
# 1 95 98 14.07398 26.2241
#
# Abbreviations:
# ARGPM: Australian Regulatory Guidelines for Prescription Medicines;
# ICH: International Council for Harmonisation;
# osle: Ordinary shelf life estimation (i.e. following the ICH guidance);
# RL: Release Limit;
# SL: Specification Limit;
# wisle: What-if (approach for) shelf life estimation (see ARGPM guidance).
res2
# Expected output of print(res2)
# Summary of shelf life estimation following the ARGPM
# guidance "Stability testing for prescription medicines"
#
# The best model accepted at a significance level of 0.25 has
# Different intercepts and Common slopes (acronym: dics).
#
# Worst case intercept and batch:
# RL Batch Intercept
# 1 98 b5 100.82
#
# Estimated shelf lives for the dics model:
# SL RL wisle osle
# 1 95 98 11.40993 23.60194
#
# Abbreviations:
# ARGPM: Australian Regulatory Guidelines for Prescription Medicines;
# ICH: International Council for Harmonisation;
# osle: Ordinary shelf life estimation (i.e. following the ICH guidance);
# RL: Release Limit;
# SL: Specification Limit;
# wisle: What-if (approach for) shelf life estimation (see ARGPM guidance).
res3
# Expected output of print(res3)
# Summary of shelf life estimation following the ARGPM
# guidance "Stability testing for prescription medicines"
#
# The best model accepted at a significance level of 0.25 has
# Different intercepts and Different slopes (acronym: dids).
#
# Worst case intercept and batch:
# RL Batch Intercept
# 1 98 b8 101.2594
#
# Estimated shelf lives for the dids model (for information, the results of
# the model fitted with pooled mean square error (pmse) are also shown:
# SL RL wisle wisle (pmse) osle osle (pmse)
# 1 95 98 7.619661 7.483223 15.96453 15.72348
#
# Abbreviations:
# ARGPM: Australian Regulatory Guidelines for Prescription Medicines;
# ICH: International Council for Harmonisation;
# osle: Ordinary shelf life estimation (i.e. following the ICH guidance);
# pmse: Pooled mean square error;
# RL: Release Limit;
# SL: Specification Limit;
# wisle: What-if (approach for) shelf life estimation (see ARGPM guidance).
}
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