Rubin Std Err - Comprehensive analysis results of several methods.

Currently, various methods have been proposed to handle missing data in clinical trials. Some methods assume that the missing data are missing at random (MAR), which means that it is assumed that subjects who stopped treatment would still maintain the treatment effect. In many cases, however, researchers often assume that the missing data are missing not at random (MNAR) to conduct additional sensitivity analyses. Under the MNAR assumption, whether using some conservative imputation methods such as RTB (return to baseline) method, J2R (jump to reference) method, and CR (copy reference) method, or optimistic imputation methods like multiple imputation (MI) and its derivative RD (retrieved dropout) method, biases compared to the true treatment effect can occur in some scenarios. This paper aims to propose a method that can impute results while considering the occurrence of intercurrent events, thereby reducing the bias compared to the true treatment effect. This method combines the RD method with the RTB formula, reducing the biases and standard errors associated with using either method alone. Considering the differing treatment effects between RD subjects and non-RD subjects, our imputation results often align more closely with the true drug efficacy.

When dealing with missing data in clinical trials, it is often convenient to work under simplifying assumptions, such as missing at random (MAR), and follow up with sensitivity analyses to address unverifiable missing data assumptions. One such sensitivity analysis, routinely requested by regulatory agencies, is the so-called tipping point analysis, in which the treatment effect is re-evaluated after adding a successively more extreme shift parameter to the predicted values among subjects with missing data. If the shift parameter needed to overturn the conclusion is so extreme that it is considered clinically implausible, then this indicates robustness to missing data assumptions. Tipping point analyses are frequently used in the context of continuous outcome data under multiple imputation. While simple to implement, computation can be cumbersome in the two-way setting where both comparator and active arms are shifted, essentially requiring the evaluation of a two-dimensional grid of models. We describe a computationally efficient approach to performing two-way tipping point analysis in the setting of continuous outcome data with multiple imputation. We show how geometric properties can lead to further simplification when exploring the impact of missing data. Lastly, we propose a novel extension to a multi-way setting which yields simple and general sufficient conditions for robustness to missing data assumptions.

The National Treatment Purchase Fund (NTPF) is responsible for the collection, collation and validation of Inpatient, Day Case and Outpatient waiting lists. The IPDC GI Endoscopy Waiting List Open Data report shows the total number of people waiting, across the various time bands, for GI Endoscopy treatment. The Children’s Health Act 2018 came into effect on 1st January 2019. Under this act, Children’s Health Ireland was established and all assets, liabilities and records were transferred from Our Lady’s Children’s Hospital Crumlin, Temple Street Children’s University Hospital and National Childrens Hospital at Tallaght University Hospital to the new body. From 1st January 2019, all NTPF reports reflect this change and data from the three sites of Children’s Health Ireland are reported as one entity. On the 31st of July 2019 Children's Health Ireland opened a new Paediatric Outpatient Department and Urgent Care Centre at CHI Connolly in Blanchardstown. The waiting lists for this site are incorporated into the Children's Health Ireland figures. Please note that NTPF does not collect activity data, i.e., numbers treated or removed. A snapshot of the number of patients waiting in each hospital is collected and published, monthly, on the NTPF website. Boards and management of individual public hospitals are responsible for the accuracy and the integrity of patient data submitted to NTPF.

United States Avg Weekly Earnings: RT: Window Treatment & Others data was reported at 581.490 USD in Mar 2025. This records an increase from the previous number of 576.470 USD for Feb 2025. United States Avg Weekly Earnings: RT: Window Treatment & Others data is updated monthly, averaging 478.150 USD from Mar 2006 (Median) to Mar 2025, with 229 observations. The data reached an all-time high of 821.670 USD in Apr 2020 and a record low of 327.290 USD in Nov 2010. United States Avg Weekly Earnings: RT: Window Treatment & Others data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Average Weekly Earnings.

Japan Things To Do: Next Time: Total: Medical Check-Up/Treatment data was reported at 38.000 Person in Mar 2018. This records a decrease from the previous number of 178.000 Person for Dec 2017. Japan Things To Do: Next Time: Total: Medical Check-Up/Treatment data is updated quarterly, averaging 184.000 Person from Mar 2014 (Median) to Mar 2018, with 17 observations. The data reached an all-time high of 234.000 Person in Mar 2016 and a record low of 38.000 Person in Mar 2018. Japan Things To Do: Next Time: Total: Medical Check-Up/Treatment data remains active status in CEIC and is reported by Ministry of Land, Infrastructure, Transport and Tourism. The data is categorized under Global Database’s Japan – Table JP.Q038: Tourism and Leisure: Things To Do: Next Visit.

LSM Std Err-Comprehensive analysis results of several methods.

United States AHE: PW: Mfg: Durable: Coating, Engraving & Heat Treating Metals data was reported at 24.200 USD in Mar 2025. This records a decrease from the previous number of 24.380 USD for Feb 2025. United States AHE: PW: Mfg: Durable: Coating, Engraving & Heat Treating Metals data is updated monthly, averaging 14.000 USD from Jan 1990 (Median) to Mar 2025, with 423 observations. The data reached an all-time high of 24.380 USD in Feb 2025 and a record low of 8.640 USD in Jan 1990. United States AHE: PW: Mfg: Durable: Coating, Engraving & Heat Treating Metals data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Average Hourly Earnings: Production Workers.

Bias - Comprehensive analysis results of several methods.

Kyrgyzstan GDP: Year to Date: GVA: NACE 2: Water Supply and Waste Treatment data was reported at 809.700 KGS mn in Mar 2025. This records a decrease from the previous number of 3,011.900 KGS mn for Dec 2024. Kyrgyzstan GDP: Year to Date: GVA: NACE 2: Water Supply and Waste Treatment data is updated quarterly, averaging 807.600 KGS mn from Mar 2012 (Median) to Mar 2025, with 53 observations. The data reached an all-time high of 3,011.900 KGS mn in Dec 2024 and a record low of 173.600 KGS mn in Mar 2012. Kyrgyzstan GDP: Year to Date: GVA: NACE 2: Water Supply and Waste Treatment data remains active status in CEIC and is reported by National Statistical Committee of the Kyrgyz Republic. The data is categorized under Global Database’s Kyrgyzstan – Table KG.A005: GDP: by Industry: Gross Value Added: Current Price: Year-to-Date.

Japan Things To Do: Bef Visit: Spain: Medical Check-Up/Treatment data was reported at 0.000 Person in Mar 2018. This stayed constant from the previous number of 0.000 Person for Dec 2017. Japan Things To Do: Bef Visit: Spain: Medical Check-Up/Treatment data is updated quarterly, averaging 0.000 Person from Mar 2015 (Median) to Mar 2018, with 13 observations. The data reached an all-time high of 2.000 Person in Sep 2017 and a record low of 0.000 Person in Mar 2018. Japan Things To Do: Bef Visit: Spain: Medical Check-Up/Treatment data remains active status in CEIC and is reported by Ministry of Land, Infrastructure, Transport and Tourism. The data is categorized under Global Database’s Japan – Table JP.Q036: Tourism and Leisure: Things To Do: Before Visiting.

Japan Things To Do: Bef Visit: Canada: Medical Check-Up/Treatment data was reported at 0.000 Person in Mar 2018. This stayed constant from the previous number of 0.000 Person for Dec 2017. Japan Things To Do: Bef Visit: Canada: Medical Check-Up/Treatment data is updated quarterly, averaging 1.000 Person from Mar 2014 (Median) to Mar 2018, with 17 observations. The data reached an all-time high of 2.000 Person in Mar 2015 and a record low of 0.000 Person in Mar 2018. Japan Things To Do: Bef Visit: Canada: Medical Check-Up/Treatment data remains active status in CEIC and is reported by Ministry of Land, Infrastructure, Transport and Tourism. The data is categorized under Global Database’s Japan – Table JP.Q036: Tourism and Leisure: Things To Do: Before Visiting.

Japan Things To Do: Bef Visit: Germany: Medical Check-Up/Treatment data was reported at 0.000 Person in Mar 2018. This stayed constant from the previous number of 0.000 Person for Dec 2017. Japan Things To Do: Bef Visit: Germany: Medical Check-Up/Treatment data is updated quarterly, averaging 0.000 Person from Mar 2014 (Median) to Mar 2018, with 17 observations. The data reached an all-time high of 2.000 Person in Jun 2015 and a record low of 0.000 Person in Mar 2018. Japan Things To Do: Bef Visit: Germany: Medical Check-Up/Treatment data remains active status in CEIC and is reported by Ministry of Land, Infrastructure, Transport and Tourism. The data is categorized under Global Database’s Japan – Table JP.Q036: Tourism and Leisure: Things To Do: Before Visiting.

We develop a Bayesian nonparametric model for a longitudinal response in the presence of nonignorable missing data. Our general approach is to first specify a working model that flexibly models the missingness and full outcome processes jointly. We specify a Dirichlet process mixture of missing at random (MAR) models as a prior on the joint distribution of the working model. This aspect of the model governs the fit of the observed data by modeling the observed data distribution as the marginalization over the missing data in the working model. We then separately specify the conditional distribution of the missing data given the observed data and dropout. This approach allows us to identify the distribution of the missing data using identifying restrictions as a starting point. We propose a framework for introducing sensitivity parameters, allowing us to vary the untestable assumptions about the missing data mechanism smoothly. Informative priors on the space of missing data assumptions can be specified to combine inferences under many different assumptions into a final inference and accurately characterize uncertainty. These methods are motivated by, and applied to, data from a clinical trial assessing the efficacy of a new treatment for acute schizophrenia. Supplementary materials for this article are available online.

Japan Things To Do: Bef Visit: France: Medical Check-Up/Treatment data was reported at 1.000 Person in Mar 2018. This stayed constant from the previous number of 1.000 Person for Dec 2017. Japan Things To Do: Bef Visit: France: Medical Check-Up/Treatment data is updated quarterly, averaging 0.000 Person from Mar 2014 (Median) to Mar 2018, with 17 observations. The data reached an all-time high of 1.000 Person in Mar 2018 and a record low of 0.000 Person in Sep 2017. Japan Things To Do: Bef Visit: France: Medical Check-Up/Treatment data remains active status in CEIC and is reported by Ministry of Land, Infrastructure, Transport and Tourism. The data is categorized under Global Database’s Japan – Table JP.Q036: Tourism and Leisure: Things To Do: Before Visiting.

Japan Things To Do: Next Time: South Korea: Medical Check-Up/Treatment data was reported at 1.000 Person in Mar 2018. This records a decrease from the previous number of 49.000 Person for Dec 2017. Japan Things To Do: Next Time: South Korea: Medical Check-Up/Treatment data is updated quarterly, averaging 54.000 Person from Mar 2014 (Median) to Mar 2018, with 17 observations. The data reached an all-time high of 82.000 Person in Mar 2016 and a record low of 1.000 Person in Mar 2018. Japan Things To Do: Next Time: South Korea: Medical Check-Up/Treatment data remains active status in CEIC and is reported by Ministry of Land, Infrastructure, Transport and Tourism. The data is categorized under Global Database’s Japan – Table JP.Q038: Tourism and Leisure: Things To Do: Next Visit.

Things To Do: Next Time: Germany: Medical Check-Up/Treatment data was reported at 0.000 Person in Mar 2018. This records a decrease from the previous number of 1.000 Person for Dec 2017. Things To Do: Next Time: Germany: Medical Check-Up/Treatment data is updated quarterly, averaging 1.000 Person from Mar 2014 (Median) to Mar 2018, with 17 observations. The data reached an all-time high of 2.000 Person in Sep 2015 and a record low of 0.000 Person in Mar 2018. Things To Do: Next Time: Germany: Medical Check-Up/Treatment data remains active status in CEIC and is reported by Ministry of Land, Infrastructure, Transport and Tourism. The data is categorized under Global Database’s Japan – Table JP.Q038: Tourism and Leisure: Things To Do: Next Visit.

Japan Things To Do: Next Time: Hong Kong: Medical Check-Up/Treatment data was reported at 2.000 Person in Mar 2018. This records a decrease from the previous number of 14.000 Person for Dec 2017. Japan Things To Do: Next Time: Hong Kong: Medical Check-Up/Treatment data is updated quarterly, averaging 7.000 Person from Mar 2014 (Median) to Mar 2018, with 17 observations. The data reached an all-time high of 14.000 Person in Dec 2017 and a record low of 2.000 Person in Mar 2018. Japan Things To Do: Next Time: Hong Kong: Medical Check-Up/Treatment data remains active status in CEIC and is reported by Ministry of Land, Infrastructure, Transport and Tourism. The data is categorized under Global Database’s Japan – Table JP.Q038: Tourism and Leisure: Things To Do: Next Visit.

Japan Things To Do: Next Time: China: Medical Check-Up/Treatment data was reported at 17.000 Person in Mar 2018. This records a decrease from the previous number of 38.000 Person for Dec 2017. Japan Things To Do: Next Time: China: Medical Check-Up/Treatment data is updated quarterly, averaging 38.000 Person from Mar 2014 (Median) to Mar 2018, with 17 observations. The data reached an all-time high of 50.000 Person in Jun 2017 and a record low of 17.000 Person in Mar 2018. Japan Things To Do: Next Time: China: Medical Check-Up/Treatment data remains active status in CEIC and is reported by Ministry of Land, Infrastructure, Transport and Tourism. The data is categorized under Global Database’s Japan – Table JP.Q038: Tourism and Leisure: Things To Do: Next Visit.

Japan Things To Do: Next Time: Thailand: Medical Check-Up/Treatment data was reported at 1.000 Person in Mar 2018. This records a decrease from the previous number of 12.000 Person for Dec 2017. Japan Things To Do: Next Time: Thailand: Medical Check-Up/Treatment data is updated quarterly, averaging 7.000 Person from Mar 2014 (Median) to Mar 2018, with 17 observations. The data reached an all-time high of 12.000 Person in Dec 2017 and a record low of 1.000 Person in Mar 2018. Japan Things To Do: Next Time: Thailand: Medical Check-Up/Treatment data remains active status in CEIC and is reported by Ministry of Land, Infrastructure, Transport and Tourism. The data is categorized under Global Database’s Japan – Table JP.Q038: Tourism and Leisure: Things To Do: Next Visit.