Description Usage Format Details Source Examples
Randomized clinical trials of at least 12 weeks duration assessing the effect of green tea consumption on weight loss.
1 |
A data frame with 14 observations on the following 9 variables.
study | character | Name of study or principal investigator |
year | numeric (integer) | Year (optional) |
outlook | factor | Denotes whether a study is unpublished, and if so, what outlook it has. |
ctrl.n | numeric (integer) | The sample size of the control arm. |
expt.n | numeric (integer) | The sample size of the experimental arm. |
ctrl.mean | numeric | The mean effect within the control arm. |
expt.mean | numeric | The mean effect within the experimental arm. |
ctrl.sd | numeric | The standard deviation of the outcome within the control arm. |
expt.sd | numeric | The standard deviation of the outcome within the experimental arm. |
The outlook of a study can be one of the following: published
, very positive
, positive
, negative
, very negative
, current effect
, no effect
, very positive CL
, positive CL
, negative CL
, or very negative CL
.
In this setting, a more negative change in outcome is desired; specify the option higher.is.better=FALSE
for the function forestsens()
.
Jurgens TM, Whelan AM, Killian L, Doucette S, Kirk S, Foy E. "Green tea for weight loss and weight maintenance in overweight or obese adults." Cochrane Database of Systematic Reviews 2012, Issue 12. Art. No.: CD008650. DOI: 10.1002/14651858.CD008650.pub2.
Figure 6. Forest plot of comparison: 1 Primary outcomes, outcome: 1.2Weight loss studies conducted in/outside Japan.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | data(greentea)
greentea
forestsens(greentea, binary=FALSE, mean.sd=TRUE, higher.is.better=FALSE)
# To fix the random number seed to make the results reproducible.
forestsens(greentea, binary=FALSE, mean.sd=TRUE, higher.is.better=FALSE, random.number.seed=52)
# To modify the outlooks of all unpublished studies to, say, "negative".
forestsens(greentea, binary=FALSE,mean.sd=TRUE,higher.is.better=FALSE,random.number.seed=52,
outlook="negative")
# To modify the outlooks of all unpublished studies to, say, "negative", and
# overruling the default standardized mean difference (SMD) assigned to "negative".
# (In this case, for a negative outlook we might assign a positive SMD, which corresponds to
# having weight loss under green tea treatment less than weight loss under control treatment,
# i.e. the green tea treatment is less effective at achieving weight loss than control treatment.
forestsens(greentea, binary=FALSE, mean.sd=TRUE, higher.is.better=FALSE,random.number.seed=52,
outlook="negative", smd.neg=0.4)
# To generate a forest plot for each of the ten default outlooks defined by forestsens().
forestsens(greentea, binary=FALSE, mean.sd=TRUE, higher.is.better=FALSE, random.number.seed=52,
all.outlooks=TRUE)
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