Description Usage Format Details Source Examples
Randomized clinical trials comparing duodenal ulcer acute healing among (1) patients on ulcer healing drug + Helicobacter pylori eradication therapy vs. (2) patients ulcer healing drug alone. The event counts represent the numbers of patients not healed.
1 |
A data frame with 33 observations on the following 7 variables.
study | character | Name of study or principal investigator |
year | numeric | Year (optional) |
outlook | factor | Denotes whether a study is unpublished, and if so, what outlook it has. |
ctrl.n | numeric | The sample size of the control arm. |
expt.n | numeric | The sample size of the experimental arm. |
ctrl.events | numeric | The number of (undesired) events within the control arm. |
expt.events | numeric | The number of (undesired) events 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
.
Since the outcome event is undesired, when using the function forestsens()
, specify the option higher.is.better=FALSE
.
Ford AC, Delaney B, Forman D, Moayyedi P. "Eradication therapy for peptic ulcer disease in Helicobacter pylori positive patients." Cochrane Database of Systematic Reviews 2006, Issue 2. Art No.: CD003840. DOI: 10.1002/14651858.CD003840.pub4.
Figure 3. Forest plot of comparison: 1 duodenal ulcer acute healing hp eradication + ulcer healing drug vs. ulcer healing drug alone, outcome: 1.1 Proportion not healed.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | data(Hpylori)
Hpylori
forestsens(table=Hpylori, binary=TRUE, higher.is.better=FALSE, scale=0.8)
# To fix the random number seed to make the results reproducible.
forestsens(table=Hpylori, binary=TRUE, higher.is.better=FALSE, scale=0.8,
random.number.seed=106)
# To modify the outlooks of all unpublished studies to, say, "very negative".
forestsens(table=Hpylori, binary=TRUE, higher.is.better=FALSE, scale=0.8,
random.number.seed=106, outlook="very negative")
# To modify the outlooks of all unpublished studies to, say, "very negative",
# and overruling the default relative risk assigned to "very negative".
forestsens(table=Hpylori, binary=TRUE, higher.is.better=FALSE, scale=0.8,
random.number.seed=106, outlook="very negative", rr.vneg=2.5)
# To generate a forest plot for each of the ten default outlooks
# defined by forestsens().
forestsens(table=Hpylori, binary=TRUE, higher.is.better=FALSE, scale=0.8,
random.number.seed=106, all.outlooks=TRUE)
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