Description Usage Arguments Value Author(s) See Also Examples
Generate and print summaries of "multiPIM"
objects (which result from calling either the multiPIM
or the multiPIMboot
function). Summaries may be of type "statistical", "time" or "both" (default). Statistical summaries contain, for each exposure-outcome pair, the parameter estimate, the standard error, the test statistic, the unadjusted p-value, and the Bonferroni-adjusted p-value. Time summaries contain a breakdown by g vs. Q modeling, and (if super learning was used to generate the "multiPIM"
object) by super learner candidate, of the time taken to run multiPIM
.
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## S3 method for class 'multiPIM'
summary(object,
type = c("both", "statistical", "time"),
use.plug.in.se = is.null(object$boot.param.array),
alternative.se.matrix = NULL,
two.sided.p.vals = TRUE,
bf.multiplier = object$num.exp * object$num.out,
by.exposure = TRUE,
digits = 4,
...)
## S3 method for class 'summary.multiPIM'
print(x, by.exposure, digits, ...)
|
object |
an object of class |
type |
The type of summary required. Default is to include both statistical and timing information in the summary. |
use.plug.in.se |
logical value indicating whether the plug-in standard errors are to be used. Defaults to |
alternative.se.matrix |
matrix of standard errors which were obtained by the user through some method other than the normal plug-in (from |
two.sided.p.vals |
logical value. Should p-values be two-sided (for |
bf.multiplier |
what number should p-values be multiplied by in doing the Bonferroni Correction. Defaults to the number of exposure-outcome pairs. |
by.exposure |
logical value. If the summary is printed, and if there is more than one exposure AND more than one outcome, should each table correspond to the exposure-outcome pairs involving each exposure (for |
digits |
passed to |
x |
an object of class |
... |
for the summary method: currently ignored. For the print method: passed to |
For the summary method:
An object of class "summary.multiPIM"
, which will have different slots depending on the value of the type
argument.
The object will always have the following slots (regardless of the value of type
):
type |
the value of the type argument to summary. |
digits |
integer value which will be the default value passed to |
call |
a copy of the call which was used to generate the |
If type
is "statistical"
or "both"
, the result of summary will in addition have the following slots:
summary.array |
a three-dimensional array containing the information which can be used to build summary tables (see below). |
two.sided.p.vals |
logical value indicating whether p-values used are two-sided (for |
stand.err.type |
the type of standard error which has been used to generate this summary object: either |
bf.multiplier |
the value of the bf.multiplier argument |
by.exposure |
logical value which will be used by default when this object is printed to decide whether the tables should be arranged by exposure (for |
Details for the summary.array
slot: the first dimension corresponds to the exposures (columns of A from the "multiPIM"
object for which the summary is being generated), the second dimension to the outcomes (columns of Y) and the third dimension has length 5 and corresponds to the 5 relevant attributes for each exposure-outcome pair (i.e. the parameter estimate, the standard error of that estimate, the test statistic, the unadjusted p-value and the Bonferroni-adjusted p-value, in that order). Thus, summary.array[1,2,3]
would be the test statistic for the pair consisting of the first exposure (first column of A) and the 2nd outcome (2nd column of Y), while summary.array[3,2,1]
would be the parameter estimate for the pair consisting of the 3rd exposure and the 2nd outcome. To access the matrix containing all unadjusted p-values, use summary.array[,,4]
, to access the matrix consisting of everything that involves the fourth outcome use summary.array[,4,]
.
If type
is "time"
or "both"
, the result of summary will in addition have the following slots:
main.time |
total time (in seconds) taken to generate the multiPIM result which is being summarized. |
g.time |
time in seconds taken for running g models. |
Q.time |
time in seconds taken for running Q models. |
g.Q.time.frame |
data frame containing breakdown of total time by g vs. Q modeling, with seconds and percentages |
g.sl.time |
if g.method is "sl", time in seconds taken for running cross-validation of g models. |
Q.sl.time |
if Q.method is "sl", time in seconds taken for running cross-validation of Q models. |
g.sl.xval.time.mat |
if super learning was used for g, a matrix containing a breakdown by super learner candidate of the time taken for cross-validation of g models, with seconds and percentages. |
Q.sl.xval.time.mat |
if super learning was used for Q, a matrix containing a breakdown by super learner candidate of the time taken for cross-validation of Q models, with seconds and percentages. |
Print method:
The print method returns its first argument (x
, which should be an object of class "summary.multiPIM"
) invisibly.
Stephan Ritter, with design contributions from Alan Hubbard and Nicholas Jewell.
multiPIM
and multiPIMboot
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | ## load example from multiPIM help file
example(multiPIM)
## The results can also be displayed by outcome instead of by exposure:
summary(result, by.exposure = FALSE)
## now each table corresponds to all the pairs involving a single outcome
## may be best to store the summary object
sum.obj <- summary(result, by.exposure = FALSE)
sum.obj
## now the print method can be used to overide the values for
## by.exposure and digits (but not the other arguments):
print(sum.obj, by.exposure = TRUE, digits = 3)
## also can hand pick the info that we want from the summary.array slot
## e.g. let's say we are interested in all of the standard errors:
sum.obj$summary.array[,,2]
## or we are only interested in the exposure1-outcome2 pair:
sum.obj$summary.array[1,2,]
## or by name
sum.obj$summary.array["A1","Y2",]
|
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