| 1. |
- Johansson, Per, et al.
(författare)
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Replik till Åke Dahlberg
- 2008
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Ingår i: Arbetsmarknad & Arbetsliv. - Karlstad : Karlstads universitet. - 1400-9692 .- 2002-343X. ; 14:4, s. 75-79
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Replik till Åke Dahlbergs kritik mot utvärderingen av "Arbetstorget för erfarna" (publicerad i Arbetsmarknad & Arbetsliv 2008, vol 14, nr 3, s 67-78)
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| 2. |
- Johansson, Per, et al.
(författare)
-
Replik till Åke Dahlerg.
- 2008
-
Ingår i: Arbetsmarknad & Arbetsliv. - Karlstad : Karlstads universitet. - 1400-9692 .- 2002-343X. ; 14:4, s. 75-79
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Tidskriftsartikel (populärvet., debatt m.m.)
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| 3. |
- Langenskiöld, Sophie, et al.
(författare)
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Outcome-free Design of Observational Studies : Peer Influence on Smoking
- 2008
-
Ingår i: Annales d'économie et de statistique (Annals of Economics and Statistics). - : JSTOR. - 0769-489X. ; :91/92, s. 107-125
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- For estimating causal effects of treatments, randomized experiments are appropriately considered the gold standard, although they are often infeasible for a variety of reasons. Nevertheless, nonrandomized studies can and should be designed to approximate randomized experiments by using only background information to create subgroups of similar treated and control units, where "similar" here refers to their distributions of background variables. This activity should be conducted without access to any outcome data to assure the objectivity of the design. In many situations, these goals can be accomplished using propensity score methods, as illustrated here in the context of a study on whether nonsmoking Harvard freshmen are influenced by their smoking peers. In that study, propensity score methods were used to create matched groups of treated units (rooming with at least one smoker) and control units (rooming with only non-smokers) who are at least as similar with respect to their distributions of observed background characteristics as if they had been randomized, thereby approximating a randomized experiment with respect to the observed covariates.
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