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Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

ABSTRACT: Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements.

SUBMITTER: Xu C

PROVIDER: S-EPMC3798038 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

Xu Chonggang C Gertner George G

Computational statistics & data analysis 20110101 1

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions ...[more]

PMID: 24143037

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Project description:BACKGROUND:Previous studies have demonstrated that patients have poor understanding of the discharge instructions provided from the emergency department (ED). The aims of this study are to determine if patient factors, such as income and level of education, correlate with patient understanding of discharge instructions and to explore if different patient populations prefer different resources for receiving discharge instructions. METHODS:We conducted live observations of physicians providing discharge instructions in the ED to 100 patients followed by a patient survey to determine their understanding in four domains (diagnosis, treatment plan, follow-up instructions, and return to ED (RTED) instructions) and collect patient demographics. We enrolled patients over the age of 18 being discharged home. We excluded non-English- or French-speaking patients and those with significant psychiatric history or cognitive impairment. We performed a two-way ANOVA analysis of patient factors and patient understanding. RESULTS:We found that patients had poor understanding of discharge instructions, ranging from 24.0% having poor understanding of their follow-up plan to 64.0% for RTED instructions. Almost half (42%) of patients did not receive complete discharge instructions. Lower income was correlated with a significant decrease in patient understanding of discharge diagnosis (p?=?0.01) and RTED instructions (p?=?0.04). Patients who did not complete high school trended towards lower levels of understanding of their diagnosis and treatment plan (p?=?0.06). Lower income patients had a preference for receiving a follow-up phone call by a nurse, while higher income patients preferred online resources. CONCLUSIONS:Lower income patients and those who have not completed high school are at a higher risk of poor understanding discharge instructions. As new technological solutions emerge to aid patient understanding of discharge instructions, our study suggests they may not aid those who are at the highest risk of failing to understand their instructions.

Dataset Information

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

Publications

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

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