Meta analisis caninos

Uribe SE, Galdames V

Paquetes

library("dplyr")

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

library("meta")

Loading 'meta' package (version 4.5-0).

library("ggplot2")
library("metafor")

Loading required package: Matrix
Loading 'metafor' package (version 1.9-9). For an overview 
and introduction to the package please type: help(metafor).

Attaching package: ‘metafor’

The following objects are masked from ‘package:meta’:

    baujat, forest, funnel, funnel.default, labbe, radial, trimfill

Cita de paquetes

citation(package = "dplyr", lib.loc = NULL, auto = NULL)

To cite package ‘dplyr’ in publications use:

  Hadley Wickham and Romain Francois (2015). dplyr: A Grammar of Data Manipulation. R package version 0.4.3.
  https://CRAN.R-project.org/package=dplyr

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {dplyr: A Grammar of Data Manipulation},
    author = {Hadley Wickham and Romain Francois},
    year = {2015},
    note = {R package version 0.4.3},
    url = {https://CRAN.R-project.org/package=dplyr},
  }

citation(package = "meta", lib.loc = NULL, auto = NULL)

To cite package ‘meta’ in publications use:

  Guido Schwarzer (2016). meta: General Package for Meta-Analysis. R package version 4.5-0.
  https://CRAN.R-project.org/package=meta

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {meta: General Package for Meta-Analysis},
    author = {Guido Schwarzer},
    year = {2016},
    note = {R package version 4.5-0},
    url = {https://CRAN.R-project.org/package=meta},
  }

citation(package = "ggplot2", lib.loc = NULL, auto = NULL)

To cite ggplot2 in publications, please use:

  H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2009.

A BibTeX entry for LaTeX users is

  @Book{,
    author = {Hadley Wickham},
    title = {ggplot2: Elegant Graphics for Data Analysis},
    publisher = {Springer-Verlag New York},
    year = {2009},
    isbn = {978-0-387-98140-6},
    url = {http://ggplot2.org},
  }

citation(package = "metafor", lib.loc = NULL, auto = NULL)

To cite the metafor package in publications, please use:

  Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software,
  36(3), 1-48. URL: http://www.jstatsoft.org/v36/i03/

A BibTeX entry for LaTeX users is

  @Article{,
    title = {Conducting meta-analyses in {R} with the {metafor} package},
    author = {Wolfgang Viechtbauer},
    journal = {Journal of Statistical Software},
    year = {2010},
    volume = {36},
    number = {3},
    pages = {1--48},
    url = {http://www.jstatsoft.org/v36/i03/},
  }

Dataset

str(df)

'data.frame':   32 obs. of  19 variables:
 $ Tipo         : Factor w/ 2 levels "binaria","continua": 1 1 1 1 1 1 1 1 1 1 ...
 $ Resultado    : Factor w/ 9 levels "Ancho de corona",..: 8 8 8 8 8 8 6 6 6 6 ...
 $ Autor        : Factor w/ 10 levels "Alqerban  2011 A",..: 2 4 9 10 5 6 2 4 9 10 ...
 $ Año          : int  2011 2011 2012 2012 2013 2015 2011 2011 2012 2012 ...
 $ n..evaluados : int  30 30 73 754 39 406 30 30 73 754 ...
 $ n..impactados: int  30 30 73 754 39 406 30 30 73 754 ...
 $ Si           : int  9 9 22 324 4 124 14 13 NA 317 ...
 $ No           : int  21 21 51 430 35 282 17 17 NA 437 ...
 $ Si.CBCT      : int  NA NA NA NA 7 NA 12 10 20 308 ...
 $ No.CBCT      : int  NA NA NA NA 32 NA 18 20 53 446 ...
 $ n.Acc        : int  NA NA NA NA NA NA NA NA NA NA ...
 $ Promedio.Acc : num  NA NA NA NA NA NA NA NA NA NA ...
 $ DE.Acc       : num  NA NA NA NA NA NA NA NA NA NA ...
 $ n.Scan       : int  NA NA NA NA NA NA NA NA NA NA ...
 $ Promedio.Scan: num  NA NA NA NA NA NA NA NA NA NA ...
 $ DE.Scan      : num  NA NA NA NA NA NA NA NA NA NA ...
 $ n.pano       : int  NA NA NA NA NA NA NA NA NA NA ...
 $ promedio.pano: num  NA NA NA NA NA NA NA NA NA NA ...
 $ DS.pano      : num  NA NA NA NA NA NA NA NA NA NA ...

MA

Preparación para el MA

Odds ratio MA

_s_ummary _m_easure = OR with _I_nverse variance method ### MA Rebsorción radicular IL #### Datos Rebsorción radicular IL

Meta analisis Rebsorción radicular IL

m1

     OR           95%-CI     z  p-value
 0.5224 [0.1397; 1.9532] -0.96   0.3346

Details:
- Inverse variance method

Gráfico Forest Plot Rebsorción radicular IL

MA Localización palatina

Datos Localización palatina

Meta analisis Rebsorción radicular IL

m1

      OR           95%-CI %W(fixed) %W(random)
1 1.2353 [0.4469; 3.4148]       3.6        3.6
2 1.5294 [0.5364; 4.3605]       3.4        3.4
3 1.0504 [0.8558; 1.2893]      88.6       88.6
4 1.1161 [0.4453; 2.7972]       4.4        4.4

Number of studies combined: k = 4

                        OR           95%-CI    z  p-value
Fixed effect model   1.073 [0.8847; 1.3012] 0.72   0.4742
Random effects model 1.073 [0.8847; 1.3012] 0.72   0.4742

Quantifying heterogeneity:
tau^2 = 0; H = 1.00 [1.00; 1.11]; I^2 = 0.0% [0.0%; 18.2%]

Test of heterogeneity:
    Q d.f.  p-value
 0.56    3   0.9051

Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2

Gráfico Forest Plot Localizacionpalatina

MA Localización vestibular

Datos Localización vestibular

Meta analisis Localizacionvestibular

m1

      OR           95%-CI %W(fixed) %W(random)
1 0.3750 [0.1182; 1.1902]       3.2       10.8
2 0.3269 [0.1035; 1.0322]       3.2       10.9
3 0.5443 [0.4385; 0.6757]      89.9       65.9
4 1.3362 [0.4636; 3.8515]       3.8       12.5

Number of studies combined: k = 4

                         OR           95%-CI     z  p-value
Fixed effect model   0.5475 [0.4460; 0.6720] -5.76 < 0.0001
Random effects model 0.5536 [0.3684; 0.8317] -2.85   0.0044

Quantifying heterogeneity:
tau^2 = 0.0533; H = 1.14 [1.00; 2.92]; I^2 = 23.4% [0.0%; 88.3%]

Test of heterogeneity:
    Q d.f.  p-value
 3.92    3   0.2706

Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2

Gráfico Forest Plot Localizacionvestibular

MA Localización en linea con el arco

Datos Localización en linea con el arco

Meta analisis Localizacionenlineaconelarco

m1

      OR           95%-CI %W(fixed) %W(random)
1 1.9023 [0.6171; 5.8635]       3.7       18.1
2 1.9023 [0.6171; 5.8635]       3.7       18.1
3 0.7182 [0.5714; 0.9027]      89.9       49.1
4 0.5224 [0.1397; 1.9532]       2.7       14.6

Number of studies combined: k = 4

                         OR           95%-CI     z  p-value
Fixed effect model   0.7654 [0.6162; 0.9507] -2.42   0.0156
Random effects model 0.9763 [0.5406; 1.7633] -0.08   0.9367

Quantifying heterogeneity:
tau^2 = 0.1715; H = 1.37 [1.00; 2.38]; I^2 = 46.9% [0.0%; 82.4%]

Test of heterogeneity:
    Q d.f.  p-value
 5.65    3   0.1302

Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2

Gráfico Forest Plot Localizacionenlineaconelarco

MA Relación de contacto %

Datos Relación de contacto %

Meta analisis Relaciondecontacto

m1

      OR            95%-CI %W(fixed) %W(random)
1 0.5224 [0.1397;  1.9532]      41.3       37.4
2 0.3056 [0.0723;  1.2914]      34.6       34.4
3 2.8000 [0.4983; 15.7344]      24.1       28.3

Number of studies combined: k = 3

                         OR           95%-CI     z  p-value
Fixed effect model   0.6505 [0.2787; 1.5183] -0.99   0.3201
Random effects model 0.6983 [0.2106; 2.3152] -0.59   0.5571

Quantifying heterogeneity:
tau^2 = 0.5477; H = 1.40 [1.00; 2.59]; I^2 = 48.8% [0.0%; 85.1%]

Test of heterogeneity:
    Q d.f.  p-value
 3.91    2   0.1417

Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2

Gráfico Forest Plot Relaciondecontacto