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outlook | `factor` | Denotes whether a study is unpublished, and if so, what outlook it has.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# To modify the outlooks of all unpublished studies to, say, "negative".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# To modify the outlooks of all unpublished studies to, say, "negative", and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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