easy_tool | R Documentation |
lasso_screenr
, logreg_screenr
and
gee_screenr
Objectseasy_tool
rescales model coefficients to whole numbers ranging from
1 to max
. Those rescaled and rounded
coefficients can be used as weights (QuestionWeights
) for each
screening question in a simplified model-based screening tool. The test
screening score for a subject is the sum of the weights for their positive
question responses.
easy_tool(object, max = 3, model = c("minAIC", "minBIC"), crossval = TRUE, ...)
object |
an object of class |
max |
(numeric) the desired maximum value for the response weights. Default: 3. |
model |
(for |
crossval |
a (logical) indicator for cross-validated ( |
... |
additional arguments passed to |
The QuestionWeights
(see Value, below) are the foundation for easy
screening. For example, the screening tool could consist of a simple
questionnaire followed by the weight for each question, expressed as a
small whole number (1, ..., max
) and/or an equal number of open
circles. The person doing the screening need
only circle the numerical weight and/or fill in the circles if and only if the
subject provides a "yes" response to a particular question. The person doing
the screening then obtains the final score for that subject by adding up the
circled numbers or counting the total number of filled-in circles. Testing is
mandatory for consenting subjects for whom that final score equals or exceeds
the chosen threshold based on the receiver-operating characteristics of
CVresults
.
The value chosen for max
involves a trade-off between the ease of
manual scoring and the degree to which the ROC from the re-scaling matches the
ROC from the model. Small values of max
make manual scoring easy, and
sufficiently large values will match the screening performance of the model
fit. It is prudent to
compare the ROCs from a few values of max
with the ROC from the model
and base the final choice on the trade-off between ease of manual scoring and
the desired combination of sensitivity and specificity.
easy_tool
returns (invisibly) an object of class easy_tool
containing:
Call
The call to easy_tool
.
varname
The names of the response and predictor variables.
QuestionWeights
Weights for the screening questions obtained
by rescaling the non-zero-valued logistic regression coefficients to whole
numbers ranging from 1 to max
.
Type
The type of test performance evaluaion ("cross-validated" or "in-sample").
Scores
A data frame containing the testing outcomes
(response
) and cross-validated scores obtained as the sums of the
weighted responses to the set of screening questions (score
).
ROC
An object of class roc
containing the
receiver-operating characteristic produced by `pROC::roc`
.
Teferi W, Gutreuter S, Bekele A et al. Adapting strategies for effective and efficient pediatric HIV case finding: Risk screening tool for testing children presenting at high-risk entry points. BMC Infectious Diseases. 2022; 22:480. http://doi.org/10.1186/s12879-022-07460-w
rescale_to_int
, ntpp.easy_tool
,
plot.easy_tool
, print.easy_tool
and
summary.easy_tool
attach(uniobj1) tool <- easy_tool(uniobj1, max = 3) methods(class = "easy_tool") summary(tool)
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