Purpose: To investigate the global burden of sepsis in hospitalized adults by updating and expanding a systematic review and meta-analysis and to compare findings with recent Institute for Health Metrics and Evaluation (IHME) sepsis estimates. Methods: Thirteen electronic databases were searched for studies on population-level sepsis incidence defined according to clinical criteria (Sepsis-1,-2: severe sepsis criteria, or sepsis-3: sepsis criteria) or relevant ICD-codes. The search of the original systematic review was updated for studies published 05/2015-02/2019 and complemented by a search targeting low-or middle-income-country (LMIC) studies published 01/1979-02/2019. We performed a random-effects meta-analysis with incidence of hospital-and ICU-treated sepsis and proportion of deaths among these sepsis cases as outcomes. Results: Of 4746 results, 28 met the inclusion criteria. 21 studies contributed data for the meta-analysis and were pooled with 30 studies from the original meta-analysis. Pooled incidence was 189 [95% CI 133, 267] hospital-treated sepsis cases per 100,000 person-years. An estimated 26.7% [22.9, 30.7] of sepsis patients died. Estimated incidence of ICU-treated sepsis was 58 [42, 81] per 100,000 person-years, of which 41.9% [95% CI 36.2, 47.7] died prior to hospital discharge. There was a considerably higher incidence of hospital-treated sepsis observed after 2008 (+ 46% compared to the overall time frame). Conclusions: Compared to results from the IHME study, we found an approximately 50% lower incidence of hospital-treated sepsis. The majority of studies included were based on administrative data, thus limiting our ability to assess temporal trends and regional differences. The incidence of sepsis remains unknown for the vast majority of LMICs, highlighting the urgent need for improved epidemiological sepsis surveillance.

Large-scale educational surveys are low-stakes assessments of educational outcomes conducted using nationally representative samples. In these surveys, students do not receive individual scores, and the outcome of the assessment is inconsequential for respondents. The low-stakes nature of these surveys, as well as variations in average performance across countries and other factors such as different testing traditions, are contributing factors to the amount of omitted responses in these assessments. While underlying reasons for omissions are not completely understood, common practice in international assessments is to employ a deterministic treatment These two model-based approaches were compared on the basis of simulated data and data from about 250,000 students from 30 Organisation for Economic Co-operation and Development (OECD) Member countries participating in an international large-scale assessment.

Even experienced operators cause a considerable number of early mechanical complications and malpositions. After two unsuccessful cannulation attempts failure and associated complications are very likely.

Item nonresponse is a common problem in educational and psychological assessments. The probability of unplanned missing responses due to omitted and not-reached items may stochastically depend on unobserved variables such as missing responses or latent variables. In such cases, missingness cannot be ignored and needs to be considered in the model. Specifically, multidimensional IRT models, latent regression models, and multiple-group IRT models have been suggested for handling nonignorable missing responses in latent trait models. However, the suitability of the particular models with respect to omitted and not-reached items has rarely been addressed. Missingness is formalized by response indicators that are modeled jointly with the researcher's target model. We will demonstrate that response indicators have different statistical properties depending on whether the items were omitted or not reached. The implications of these differences are used to derive a joint model for nonignorable missing responses with ability to appropriately account for both omitted and not-reached items. The performance of the model is demonstrated by means of a small simulation study.

Different cross‐domain trajectories in the development of students’ ability self‐concepts (ASCs) and their intrinsic valuing of math and language arts were examined in a cross‐sequential study spanning Grades 1 through 12 (n = 1,069). Growth mixture modeling analyses identified a Moderate Math Decline/Stable High Language Arts class and a Moderate Math Decline/Strong Language Arts Decline class for students’ ASC trajectories. Students’ intrinsic value trajectories included a Strong Math Decline/Language Arts Decline Leveling Off, a Moderate Math Decline/Strong Language Arts Decline, and a Stable Math and Language Arts Trajectories class. These classes differed with regard to student characteristics, including gender, family background, and math and reading aptitudes. They also resulted in different high school math course enrollments, career aspirations, and adult careers.