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While the computational cost is relatively cheap and weakly dependent on k for estimating first order effects, it remains expensive and strictly k-dependent for total effect indices.
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This paper studies the optimality of circular neighbor-balanced designs (CNBDs) for total effects when the one-sided or two-sided neighbor effects are present in the model and the observation errors are correlated according to a first-order circular autoregressive (AR(1,C)) process.
The estimated coverage probabilities for the total effect for all sample sizes for the SEM were high, ranging from 92% to 96%.
In the past, the global sensitivity analysis method for the total effect has been used for the structure learning of neural networks and various growing and pruning algorithms have been developed.
The coverage probabilities for the total effect were again ≥ 93% for both the SEM and the LMM2.
The coefficient for the total effect of being in a migrant household for teenagers is still statistically significant at 5%% (it corresponds to 0.326), but the results show that there is not a differential impact due to the fact that the household is located in a rural or urban area.
We note that for the SEM, with a sample size of 100, the power for the total effect was 65%, while the power to detect the direct and indirect effects were 26%and71%1% (data not shown), respectively.
It has a direct effect of 0.513 on "my future job" and an indirect effect of 0.09151 through out-of-school interests and 0.1714 through "my interest in science" for a total effect of 0.7759. .
Columns 5 and 6 show that both women and teenagers in migrant households have a higher knowledge of contraceptive methods: the coefficient for the total effect of being in a migrant household corresponds to 0.281, statistically significant at the 5 %, for all women and to 0.304, statistically significant at 10%%, for teenagers.
The product of the two hazard ratios yields the hazard ratio for the total effect.
The confidence criterion for the total effect of a marker pair was set to p = 10-5.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com