# [R] Help interpreting data

Matty A m@t|r|m| @end|ng |rom gm@||@com
Thu Apr 4 01:31:59 CEST 2019

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From: matty <matirimi using gmail.com>
To: r-help using r-project.org
Cc:
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Date: Wed, 3 Apr 2019 18:21:28 -0500 (CDT)
Subject: res intepretation help
Hi.. im a complete novice and am using R for my dissertation which is a
meta-analysis... im using res would like some advice on
understanding my results and what I can do with them.. the original data is
h' values (linearity of social hierarchies) i have 11
samples with 2 h' values that i am looking at my each res code has only one
h' value the h' value is places where r would be in the code... below is a
few of mu outputs.... thank you

> res(1, var.r=NULL, 6, level=95, dig = 4, verbose = TRUE, id=NULL, data =
> NULL) –
Bonanni et al 2017 La Rustica   Free-ranging submission
Mean Differences ES:

d [ 95 %CI] = Inf [ NaN , NaN ]
var(d) = NaN
p-value(d) = NaN
U3(d) = 100 %
CLES(d) = 100 %
Cliff's Delta = 1

Correlation ES:

r [ 95 %CI] = 1 [ NaN , NaN ]
var(r) = 0
p-value(r) = 0

z [ 95 %CI] = Inf [ Inf , Inf ]
var(z) = 0.3333
p-value(z) = 0

Odds Ratio ES:

OR [ 95 %CI] = Inf [ NaN , NaN ]
p-value(OR) = NaN

Log OR [ 95 %CI] = Inf [ NaN , NaN ]
var(lOR) = NaN
p-value(Log OR) = NaN

Other:

NNT = 1.25
Total N = 6
> res(0.860, var.r=NULL, 6, level=95, dig = 4, verbose = TRUE, id=NULL, data
> = NULL) –
Bonanni et al 2017 La Rustica Free-ranging aggression
Mean Differences ES:

d [ 95 %CI] = 3.3706 [ -1.135 , 7.8762 ]
var(d) = 3.0722
p-value(d) = 0.1125
U3(d) = 99.9625 %
CLES(d) = 99.1423 %
Cliff's Delta = 0.9828

Correlation ES:

r [ 95 %CI] = 0.86 [ -0.1885 , 0.9923 ]
var(r) = 0.0136
p-value(r) = 0.0752

z [ 95 %CI] = 1.2933 [ -0.1908 , 2.7775 ]
var(z) = 0.3333
p-value(z) = 0.0752

Odds Ratio ES:

OR [ 95 %CI] = 451.964 [ 0.1276 , 1600648 ]
p-value(OR) = 0.1125

Log OR [ 95 %CI] = 6.1136 [ -2.0587 , 14.2859 ]
var(lOR) = 10.1071
p-value(Log OR) = 0.1125

Other:

NNT = 1.259
Total N =

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