| Evaluación | Efecto | Edad promedio | Observaciones | Evaluación experimental | País | Intervención |
|---|---|---|---|---|---|---|
| Iacovone 2022 i | 3 | 43 | 3,960 | Si | Colombia | Componentes entrenados: Gestión + Habilidades sociales + Contabilidad |
| Iacovone 2022 ii | 10 | 43 | 3,960 | Si | Colombia | Componentes entrenados: Gestión + Habilidades sociales + Contabilidad |
| Chong 2020 | 3 | 44.5 | 678 | Si | Kirguistán | Componentes entrenados: Gestión + Habilidades sociales + Contabilidad |
| Dammert 2019 ii | 14 | 40.43 | 529 | Si | Liberia | Componentes entrenados: Gestión + Habilidades sociales + Contabilidad |
| Drexler 2014 i | -8 | 40.2 | 376 | Si | República Dominicana | Componentes entrenados: Gestión + Habilidades sociales + Contabilidad |
| Bruhn 2018 | 5 | 42.19 | 307 | Si | México | Componentes entrenados: Gestión + Habilidades sociales + Contabilidad |
| Assenova 2020 | 4 | 33.51 | 284 | No | Sudáfrica | Componentes entrenados: Gestión + Habilidades sociales + Contabilidad |
| Anderson 2022 ii | 73 | 37.7 | 267 | Si | Nigeria | Componentes entrenados: Gestión + Habilidades sociales + Contabilidad |
Graph of Effects
This graph shows the effects of [Number of Evaluations] evaluations of [Program Type] programs. The first evaluation, [Evaluation name 1], estimated an effect of [Estimated effect Eval. 1] points (graphed with the top grey circle). Because this is an estimate, there is uncertainty about what the true effect is. But we know that the true effect will probably lie between a low value of [True effect lie between – Low value, Eval. 1] and a high value of [True effect lie between – High value, Eval. 1] (graphed with the top horizontal line). We can combine the estimates from all the evaluations and compute an average effect of [Estimated effect, Average] (graphed with the black circle). There is also uncertainty about where the true average effect is. But we know that the true average effect probably lies between [True effect lie between – Low value, Average] and [True effect lie between – High value, Average] points (graphed with the bottom horizontal line).
| Evaluación | Efectos | Valor Mínimo | Valor Máximo | Peso en el efecto promedio (%) |
|---|---|---|---|---|
| Anderson 2022 ii | 73 | -76 | 222 | 0 |
| Assenova 2020 | 4 | 2 | 5 | 94 |
| Bruhn 2018 | 5 | -20 | 30 | 0 |
| Chong 2020 | 3 | -13 | 20 | 1 |
| Dammert 2019 ii | 14 | -6 | 34 | 1 |
| Drexler 2014 i | -8 | -23 | 7 | 1 |
| Iacovone 2022 i | 3 | -10 | 16 | 2 |
| Iacovone 2022 ii | 10 | -7 | 26 | 1 |
| Overall |