Multiple Imputation for Missing Data in Life Cycle Inventory

2009 ◽  
Vol 610-613 ◽  
pp. 21-27 ◽  
Author(s):  
Yu Liu ◽  
Xian Zheng Gong ◽  
Zhi Hong Wang ◽  
Wei Liu ◽  
Zuo Ren Nie
Keyword(s):  
Missing Data ◽  
Multiple Imputation ◽  
Separation Process ◽  
Iron Production ◽  
Validity And Reliability ◽  
Environmental Loads ◽  
Mineral Separation ◽  
Standard Procedures ◽  
Plausible Values

The major environmental loads of mineral separation process in China iron production (with missing data) are analyzed. And the inner relationship between these loads data is qualified and the missing data are imputed using a statistic method called multiple imputation (MI), aimed to improve the quality of LCA datasets and allow industry to easily conduct a highly reliable LCA. By using computer simulation, MI replaces each missing value with a set of plausible values which represent the uncertainty of the missing data. The multiply imputed datasets are then analyzed by the standard procedures for completing data and combining the results from these analyses. The result proves that MI Method is an effective and reasonable method to solve the problem of missing data and therefore can ensure the validity and reliability of LCA.

scholarly journals Handling missing data in a composite outcome with partially observed components: Application in clustered paediatric routine data.

2019 ◽  
Author(s):  
Susan Gachau ◽  
Edmund Njeru Njagi ◽  
Nelson Owuor ◽  
Paul Mwaniki ◽  
Matteo Quartagno ◽  
...  
Keyword(s):  
Quality Of Care ◽  
Missing Data ◽  
Multiple Imputation ◽  
Conventional Method ◽  
Routine Data ◽  
Composite Outcome ◽  
Model Framework ◽  
Composite Measures ◽  
Partially Observed

Abstract Background: In health care settings, composite measures are used to combine information from multiple quality of care measures into a single summary score. Composite scores provide global insights and trends about complex and multidimensional quality of care processes. However, missing data in subcomponents may hinder the overall reliability of the composite measures in subsequent analysis and inferences. In this study we demonstrate strategies for handling missing data in Paediatric Admission Quality of Care (PAQC) score, a composite outcome which summarizes quality of inpatient paediatric care in low income settings.Methods: We analysed routine data collected in a cluster randomized trial in 12 Kenyan hospitals. Multilevel multiple imputation (MI) within joint model framework was used to fill-in missing values in selected PAQC score subcomponents and partially observed covariates across two levels of hierarchy. We used proportional odds random intercepts and generalized estimating equations (GEE) models to analyse PAQC score before and after multiple imputation. Using a set of simulations scenario, that is, varied proportions of missingness in PAQC score subcomponents of interest under missing at random and missing completely at random mechanisms respectively, we compared the magnitude of bias in parameter estimates obtained under MI and the conventional method in addressing missing data in PAQC score components. Under the conventional method we scored all missing PAQC score components with value 0.Results: Results from observed data showed that multiple imputation of both PAQC score components and covariates yielded more accurate and precise estimates compared to complete case analysis. From the simulation study, the conventional missing data method led to significantly larger biases in estimated proportional log odds of the outcome compared to MI methods. The amount of bias increased with increase in rate of missingness with substantial variation between the missing data mechanisms under the conventional method. Conclusion: In comparison with conventional method, MI produce minimally biased estimates regardless of amount of missing data rate and underlying mechanism. We therefore recommend avoiding the conventional method in favour of multiple imputation; more research is needed to compare different ways of performing multiple imputation at the component and composite outcome level.TRIAL REGISTRATION: US National Institutes of Health-ClinicalTrials.gov identifier (NCT number) NCT02817971 . Registered September 28, 2016-retrospectively registered.

scholarly journals What difference does multiple imputation make in longitudinal modeling of EQ-5D-5L data? Empirical analyses of simulated and observed missing data patterns

2021 ◽  
Author(s):  
Inka Rösel ◽  
Lina María Serna-Higuita ◽  
Fatima Al Sayah ◽  
Maresa Buchholz ◽  
Ines Buchholz ◽  
...  
Keyword(s):  
Missing Data ◽  
Multiple Imputation ◽  
Mixed Models ◽  
Missing Values ◽  
Life Questionnaire ◽  
Related Quality ◽  
Health Related ◽  
Baseline Covariates

Abstract Purpose Although multiple imputation is the state-of-the-art method for managing missing data, mixed models without multiple imputation may be equally valid for longitudinal data. Additionally, it is not clear whether missing values in multi-item instruments should be imputed at item or score-level. We therefore explored the differences in analyzing the scores of a health-related quality of life questionnaire (EQ-5D-5L) using four approaches in two empirical datasets. Methods We used simulated (GR dataset) and observed missingness patterns (ABCD dataset) in EQ-5D-5L scores to investigate the following approaches: approach-1) mixed models using respondents with complete cases, approach-2) mixed models using all available data, approach-3) mixed models after multiple imputation of the EQ-5D-5L scores, and approach-4) mixed models after multiple imputation of EQ-5D 5L items. Results Approach-1 yielded the highest estimates of all approaches (ABCD, GR), increasingly overestimating the EQ-5D-5L score with higher percentages of missing data (GR). Approach-4 produced the lowest scores at follow-up evaluations (ABCD, GR). Standard errors (0.006–0.008) and mean squared errors (0.032–0.035) increased with increasing percentages of simulated missing GR data. Approaches 2 and 3 showed similar results (both datasets). Conclusion Complete cases analyses overestimated the scores and mixed models after multiple imputation by items yielded the lowest scores. As there was no loss of accuracy, mixed models without multiple imputation, when baseline covariates are complete, might be the most parsimonious choice to deal with missing data. However, multiple imputation may be needed when baseline covariates are missing and/or more than two timepoints are considered.

Analisis Kualitas Pelayanan Dalam Pelaksanaan Tera Dan Tera Ulang Alat Ukur, Timbang, Takar Dan Perlengkapannya (UTTP) Pada Bidang Perdagangan Dinas Koperasi, Perindustrian Dan Perdagangan Kabupaten Pacitan

2016 ◽  
Vol 3 (2) ◽  
pp. 159-173
Author(s):  
Susi Minarsih ◽  
Ary Sutrischastini
Keyword(s):  
Quality Of Service ◽  
Service Quality ◽  
Level Of Service ◽  
Research Use ◽  
Validity And Reliability ◽  
Analysis Instrument ◽  
Service Execution ◽  
Traditional Market ◽  
Convenience Sampling

The aims of this study are to measure the level of service quality and how to improve the quality of service execution in re-measurement tera and tera of UTTP in Commerce On duty Co-Operation, Industrial and Commerce Of Sub-Province of Pacitan. This research’s object is traditional market of Minulyo Pacitan as mains market in Sub-Province of Pacitan with 100 perpetrator people of sample as user/owner of UTTP (ukur,timbang, takar, dan perlengkapannya) with method intake of sampel by Convenience Sampling. The technique of collecting data uses questionnaires and direct interview. This research use qualitative analysis instrument test of validity and reliability to know valid or not and reliabel or not about the questions of questionnaire. Then, this research was done with Servqual method as instrument to do measurement of service quality. The measurement of service quality in Servqual method pursuant to five service dimension that is tangibles, responsiveness, realibility, assurance, and empathy. This research will be measured of gap 5 that is difference among performance and its expectation. Ad for yielded gap from a enumeration of Servqual 5 gap, -146 progressively lower him mount the quality of given service activities. Therefore, its needs the existence of priority repair of service quality, in this case is service of remeasurement tera and tera of UTTP at biggest difference or gap that is at variable of Responsiveness ( Energy Listen carefully) and attribute that has smallest difference that is – 0.44 at dimension question of variable of Tangibles ( Evidence Physical). Keyword: Quality Of Service, Method of Service Quality.

Validity and reliability of the French version of the Pediatric Quality of Life Inventory™ brain tumor module

2021 ◽  
Author(s):  
Maxime Caru ◽  
Sébastien Perreault ◽  
Ariane Levesque ◽  
Serge Sultan ◽  
Leandra Desjardins ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Brain Tumor ◽  
Validity And Reliability ◽  
French Version ◽  
Quality Of Life Inventory ◽  
Life Inventory

scholarly journals Validity and reliability testing of the Toddler and Infant (TANDI) Health Related Quality of Life instrument for very young children

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Janine Verstraete ◽  
Lebogang Ramma ◽  
Jennifer Jelsma
Keyword(s):  
Quality Of Life ◽  
Health Related Quality ◽  
Validity And Reliability ◽  
Spearman's Rho ◽  
Spearman’S Rho ◽  
Related Quality ◽  
Health Related ◽  
Six Dimensions ◽  
The Impact

Abstract Background Despite the high burden of disease in younger children there are few tools specifically designed to estimate Health Related Quality of Life (HRQoL) in children younger than 3 years of age. A previous paper described the process of identifying a pool of items which might be suitable for measuring HRQoL of children aged 0–3 years. The current paper describes how the items were pruned and the final draft of the measure, Toddler and Infant (TANDI) Health Related Quality of Life, was tested for validity and reliability. Methods A sample of 187 caregivers of children 1–36 months of age were recruited which included children who were either acutely ill (AI), chronically ill (CI) or from the general school going population (GP). The TANDI, an experimental version of the EQ-5D-Y proxy, included six dimensions with three levels of report and general health measured on a Visual Analogue Scale (VAS) from 0 to 100. The content validity had been established during the development of the instrument. The TANDI, Ages and Stages Questionnaire (ASQ), Faces, Leg, Activity, Cry, Consolabilty (FLACC) or Neonatal Infant Pain Scale (NIPS) and a self-designed dietary information questionnaire were administered at baseline. The TANDI was administered 1 week later in GP children to establish test-retest reliability. The distribution of dimension scores, Cronbach’s alpha, rotated varimax factor analysis, Spearman’s Rho Correlation, the intraclass correlation coefficient, Pearson’s correlation, analysis of variance and regression analysis were used to explore the reliability, and validity of the TANDI. Results Concurrent validity of the different dimensions was tested between the TANDI and other instruments. The Spearman’s Rho coefficients were significant and moderate to strong for dimensions of activity and participation and significant and weak for items of body functions. Known groups were compared and children with acute illness had the lowest ranked VAS (median 60, range 0–100), indicating worse HRQoL. The six dimensions of the TANDI were tested for internal consistency and reliability and the Cronbach’s α as 0.83. Test-retest results showed no variance for dimension scores of movement and play, and high agreement for pain (83%), relationships (87%), communication (83%) and eating (74%). The scores were highly correlated for the VAS (ICC = 0.76; p < 0.001). Conclusion The TANDI was found to be valid and reliable for use with children aged 1–36 months in South Africa. It is recommended that the TANDI be included in future research to further investigate HRQoL and the impact of interventions in this vulnerable age group. It is further recommended that future testing be done to assess the feasibility, clinical utility, and cross-cultural validity of the measure and to include international input in further development.

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