Thanks a lot David!!
metan [varlist], proportion transform(ftukey, iv) works great!
Best regards,
Nicoletta
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Note: 1 study with missing or insufficient data found; use the keepall option to include this study in the summary table and forest plot
>1 invalid name Error in ipdmetan.metan_setup
ipdmetan, study(study) ad(Data\temp\nigeria_bin21.dta, byad vars(_ES _lci _uci)) saving(Data\temp\bin21.dta, replace): glm bin21 arm01 i.Grav3Gr, fam(bin) link(log) eform
* Example generated by -dataex-. To install: ssc install dataex clear input str14 study byte(deadGrp1 totalGrp1 deadGrp2 totalGrp2) float(aliveGrp2 aliveGrp1) "study1" 1 15 5 20 15 14 "study2" 2 60 4 64 60 58 "study3" 3 22 3 24 21 19 "study4" 4 36 2 40 36 32 "study5" 5 45 1 44 43 40 end
metan deadGrp1 totalGrp1, proportion random ftt lcols(study) counts forestplot
metan deadGrp1 aliveGrp1 deadGrp2 aliveGrp2, rr random lcols(study) forestplot
Studies included: 5 Participants included: 178 Meta-analysis pooling of Freeman-Tukey transformed Proportions using the random-effects inverse-variance model with DerSimonian-Laird estimate of tau² -------------------------------------------------------------------- study | Proportion [95% Conf. Interval] % Weight ---------------------+---------------------------------------------- study1 | 0.067 0.012 0.298 8.80 study2 | 0.033 0.009 0.114 33.01 study3 | 0.136 0.047 0.333 12.70 study4 | 0.111 0.044 0.253 20.34 study5 | 0.111 0.048 0.235 25.15 ---------------------+---------------------------------------------- Overall, DL | 0.077 0.038 0.125 100.00 -------------------------------------------------------------------- Test of overall effect = 0: z = 5.597 p = 0.000 Heterogeneity measures, calculated from the data with Conf. Intervals based on Gamma (random-effects) distribution for Q --------------------------------------------------------- Measure | Value df p-value ---------------------+----------------------------------- Cochran's Q | 4.13 4 0.389 | -[95% Conf. Interval]- H | 1.016 1.000 1.695 I² (%) | 3.0% 0.0% 65.2% --------------------------------------------------------- H = relative excess in Cochran's Q over its degrees-of-freedom I² = proportion of total variation in effect estimate due to between-study heterogeneity (based on Q) Heterogeneity variance estimates ----------------------------------- Method | tau² ---------------------+------------- DL | 0.0002 ----------------------------------- invalid syntax Error in metan.BuildResultsSet (Note: meta-analysis model was fitted successfully) r(197);
* Example generated by -dataex-. To install: ssc install dataex clear input str3 studyname long n int cases "S1" 217154 422 "S10" 16557 32 "S13" 676 1 "S18" 44 1 "S26" 29 1 end
0.199% | (0.137%, | 0.272%) |
* Example generated by -dataex-. To install: ssc install dataex clear input str23 study int n byte(a b c) int d float qi byte(q1 q2 q3 q4 q5) float(r1 r2 r3 r4 r5) "Baronciani (1986) [24]" 74 13 4 8 49 .29166666 43 64 45 46 53 3.5 6 3.5 8 7 "Dura (1997) [25]" 48 3 4 14 27 1 86 89 85 77 79 12 12 12 12 12 "Evans (1999) [26]" 113 2 10 17 84 .5833333 50 68 48 42 49 7 7.5 5 4.5 4 "Foresman (2001) [27]" 139 24 43 25 47 .9166667 79 82 79 73 76 11 11 11 11 11 "Mage (1989) [28]" 122 22 5 19 76 .08333334 36 57 42 35 42 1 1.5 1.5 1 1 "Mahant (2002) [29]" 162 14 30 21 97 .8333333 64 75 73 65 68 10 10 10 10 10 "Morin (1999) [30]" 70 20 41 2 7 .5833333 50 68 55 42 52 7 7.5 7 4.5 5.5 "Muensterer (2002) [31]" 386 35 76 34 241 .75 57 71 58 46 55 9 9 8.5 8 8 "Oostenbrink (2000) [32]" 140 21 20 16 83 .29166666 43 61 42 42 47 3.5 4 1.5 4.5 3 "Salih (1994) [33]" 42 26 3 1 12 .29166666 43 57 52 46 58 3.5 1.5 6 8 9 "Tan (1988) [34]" 55 3 6 14 32 .5833333 50 61 58 42 52 7 4 8.5 4.5 5.5 "Verber (1988) [35]" 62 8 9 20 25 .29166666 43 61 45 38 46 3.5 4 3.5 2 2 end
metan a b c d, qe(q3) study( study ) or counts forestplot(astext(85) boxscale(65) spacing(0.95) leftjustify)
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