China
Africa
Explore chapters and articles related to this topic
Sampling Distribution of the Mean
Published in Marcello Pagano, Kimberlee Gauvreau, Heather Mattie, Principles of Biostatistics, 2022
Marcello Pagano, Kimberlee Gauvreau, Heather Mattie
Looking at Figures 8.3 through 8.5, we see that as the size of the samples increases, their distributions approach the shape of the population distribution pictured in Figure 8.2. Although there are still differences among the samples, the amount of variability in the estimates and s decreases. This property is known as consistency. As the samples that we select become larger and larger, the estimates of the population parameters approach their target values.
Introduction and Datasets
Published in Andrew B. Lawson, Using R for Bayesian Spatial and Spatio-Temporal Health Modeling, 2021
The first example considered is the distribution of larynx cancer cases with associated residential addresses in a study region of North West England, UK, for the period 1973 to 1984. These data were collected originally in relation to a “cluster alarm,” whereby a local incineration site was suspected to have been influential in increasing the risk of larynx cancer in its vicinity. The incidence of a “control disease” is also available in the study area: respiratory cancer. Both larynx and respiratory cancer incidence is available as residential addresses (Diggle, 1990). The purpose of the control disease is to provide a geographical control, in that the distribution of the control disease should represent the at-risk population distribution for the case disease, but not be affected by the process creating the case distribution. The choice of respiratory cancer as a control is controversial as incineration could be a source of air pollutants and respiratory cancer could have an association. Hence in this case the control provides a relative risk control, but possibly not an absolute control. To augment this dataset a synthetic variable (age at diagnosis) was added, for the purposes of exposition only.
Statistics for Genomics
Published in Altuna Akalin, Computational Genomics with R, 2020
The good thing about CLT is, as long as the sample size is large, regardless of the population distribution, the distribution of sample means drawn from that population will always be normal. In Figure 3.7, we repeatedly draw samples 1000 times with sample size ,30, and 100 from a bimodal, exponential and a uniform distribution and we are getting sample mean distributions following normal distribution.
Communication disability in Bangladesh: issues and solutions
Published in Speech, Language and Hearing, 2023
Md Jahangir Alam, Linda Hand, Elaine Ballard
The most important recommendation for the public service is for SLT services to be funded to be equitable across both urban and rural sectors and across a range of ages. It needs to also include developmental language disorders as a disability in need of intervention, hence needs to move beyond the acute health system. These points mean inclusion of SLT services into both the mainstream health system and the public education system. As noted above, rehabilitation professionals, such as SLTs, Physiotherapists, and Occupational Therapists are yet to be included in the health service structure of Bangladesh at the primary level. If SLT services were available at this level in the government health structures (particularly in the CCs in rural areas) people from rural areas would be able to access them. This would, in part, address barriers relating to geography and population distribution discussed above.
Prevalence of Refractive Error in Vientiane Province, Lao People’s Democratic Republic
Published in Ophthalmic Epidemiology, 2023
Chirag Patel, Yiran Tan, Stephen Nygaard, Brad Guo, Cesar Carrillo, Jerida Burgess, Kitar Souksamone, Kham Od Nouansavanh, Robert Casson
A total of 1625 participants were sampled and 1264 (77.5%) completed the full ophthalmic examination. Suitable refractive data were available in 1058 (65.1%) individuals; 661 were from rural villages and 397 from urban villages; 206 participants were excluded. The excluded participants had pseudophakia or aphakia and/or there was difficulty recording refraction due to corneal opacity or scarring. Therefore, the included study participants were 401 males and 657 females, with a mean age of 58.3 (SD 11.1) and 55.5 (SD 10.3) respectively. The most recent census data reveals a similar urban-rural population distribution (32.9 and 67.1% respectively).21 The male to female gender ratio in the census data was 1:1, while in this study the male to female ratio was 1:1.6. Anecdotally, this was due to invited male participants being unable to leave manual work sites to attend an eye assessment. The correlation between right and left eyes for spherical equivalent (SE) was 0.655 (p < .001). The proportions are derived taking the survey weights into consideration. The particpants’ characteristics and refractive data are shown in Supplementary Table 1.
Seropositivity to SARS-CoV-2 in Alberta, Canada in a post-vaccination period (March 2021–July 2021)
Published in Infectious Diseases, 2022
Jamil N. Kanji, Leonard T. Nguyen, Sabrina S. Plitt, Carmen L. Charlton, Jayne Fenton, Sheila Braun, Carol Marohn, Cheryl Lau, Lawrence W. Svenson, Deena Hinshaw, Christie Lutsiak, Nathan Zelyas, Michael Mengel, Graham Tipples
A limitation to this study is the use of residual blood samples for serosurveillance purposes. It may be biased towards individuals who sought health care and required clinical testing, while healthy individuals not seeking care were likely not included. To compensate, results are presented as seropositivity rather than prevalence. There was a higher proportion of samples from urban centres, where population density may have led to a higher demand for COVID-19 testing, and patients may have easier access to healthcare. To standardise the presentation of findings, we adjusted for population distribution based on census data. Furthermore, the latest census data available at the time of analysis is from 2016 (as 2021 census data is not expected until the first quarter of 2022). Thus, it is possible that variables of population distribution, sociodemographics, and income may have changed [48]. Use of census data in this manner, however, has been done in previous studies [7,49] The strengths of this study lie in the large number of samples, testing over several months and linking of results to multiple health ministry and health service databases with data on vaccination and previous NAAT.