calculateT | R Documentation |
Calculates point estimates for the stochastic threshold.
calculateT(
data,
log.model = FALSE,
p.dropout = 0.01,
pred.int = 0.95,
debug = FALSE
)
data |
data.frame with dependent and explanatory values in columns named 'Dep' and 'Exp'. |
log.model |
logical indicating if data should be log transformed. Default=FALSE. |
p.dropout |
numeric accepted risk to calculate point estimate for. Default=0.01. |
pred.int |
numeric prediction interval. Default=0.95. |
debug |
logical indicating printing debug information. |
Given a data.frame with observed values for the dependent variable
(column 'Dep') and explanatory values (column 'Exp') point estimates
corresponding to a risk level of p.dropout
are calculated
using logistic regression: glm(Dep~Exp, family=binomial("logit")
.
A conservative estimate is calculated from the pred.int
.
In addition the model parameters B0 (intercept) and B1 (slope),
Hosmer-Lemeshow test statistic (p-value), and the number of observed
and dropped out alleles is returned.
vector with named parameters
calculateDropout
, calculateAllT
,
modelDropout_gui
, plotDropout_gui
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