Sampling over time to classify or estimate a population growth curve.

2009 ◽  
pp. 227-244
Author(s):  
M. R. Binns ◽  
J. P. Nyrop ◽  
W. van der Werf
Keyword(s):  
Population Growth ◽  
Growth Curve ◽  
Over Time

scholarly journals Development of Interest and Role of Choice During Sequential Knowledge Acquisition

2018 ◽  
Author(s):  
Greta M. Fastrich ◽  
Kou Murayama
Keyword(s):  
Knowledge Acquisition ◽  
Growth Curve ◽  
School Environment ◽  
Interest Development ◽  
Growth Curve Modelling ◽  
Over Time

Interest is an important motivational element for learning in the school environment. However, little research has directly addressed how interest develops over time as knowledge accumulates. To gain a better understanding of interest development, we developed a paradigm where participants gain step-by-step information about lesser known countries. After reading each piece of information, participants rated their interest in and liking of the country. Growth-curve modelling showed that interest grows during knowledge acquisition until it eventually stalls and starts to decline. We also found that the opportunity to choose information boosted the growth in interest and delayed its decline. Further analysis revealed that people disengaged from a topic (i.e. stopped accessing information about a particular country) when their interest started to decrease.

The Psychological Well-Being of Taiwanese Youth

2009 ◽  
Vol 24 (3) ◽  
pp. 397-429 ◽  
Author(s):  
Chin-Chun Yi ◽  
Chyi-In Wu ◽  
Ying-Hwa Chang ◽  
Ming-Yi Chang
Keyword(s):  
Depressive Symptoms ◽  
Growth Curve ◽  
Panel Study ◽  
School Context ◽  
Subsequent Development ◽  
Well Being ◽  
Quadratic Growth ◽  
School Factors ◽  
Psychological Well Being ◽  
Over Time

This study examines the growth trajectory of the psychological well-being of Taiwanese adolescents from early to late adolescence. Under the competitive educational system in Taiwan, family and school context are two major loci accounting for the developmental outcome. Data are taken from the Taiwan Youth Project, which is a longitudinal panel study of 2696 students since the year 2000. The study uses individual depressive symptoms as the dependent variable. Family cohesion, family educational strategy as well as classroom effects at school are chosen to indicate the potential contextual influence. Using the latent growth curve method, the analysis confirms that family and school factors do produce different effects over time. Family context is salient at the initial status, but not for subsequent development. Class cohesion as well as adolescents' perceptions of unfairness by teachers determine the depressive level, the linear slope and the non-linear quadratic growth curve. In other words, once the adolescent gets used to junior high school, the school context tends to exert more pronounced effects. Further analysis on gender comparisons indicates that selective family and school effects are more pronounced among females, with a greater degree of depressive symptoms over time. The article concludes that while family and school have different impacts on the growth curve of individual depressive symptoms, the school context exerts salient effects over an adolescent's life course.

INDIVIDUAL PERFORMANCE OVER TIME: GROWTH CURVE APPLICATIONS.

1991 ◽  
Vol 1991 (1) ◽  
pp. 315-319
Author(s):  
David A. Hofmann ◽  
Rick Jacobs ◽  
Steve J. Gerras
Keyword(s):  
Growth Curve ◽  
Individual Performance ◽  
Over Time

The Railways, Urbanization, and Local Demography in England and Wales, 1825–1911

2010 ◽  
Vol 34 (2) ◽  
pp. 199-228
Author(s):  
Ian N. Gregory ◽  
Jordi Martí Henneberg
Keyword(s):  
World War I ◽  
Population Growth ◽  
World War ◽  
England And Wales ◽  
Rail Network ◽  
Level Data ◽  
Integrate Data ◽  
Single Set ◽  
Over Time

This article uses geographic information systems (GIS) to explore the growth of the rail network in England and Wales in the period before World War I. It uses two major GIS databases, one containing data on the growth of the rail network, including both lines and stations, and one containing parish-level populations. The parish-level data are particularly important for two reasons: they give an unparalleled level of spatial detail, and they are interpolated onto a single set of boundaries over time, which allows direct long-term comparisons. GIS's ability to integrate data allows the article to shed new light on how quickly the railways spread into the country's population. It then explores whether gaining a station made it more likely for a parish's population growth to increase and whether gaining one early was an advantage compared to gaining one relatively late. The article explores this impact at a variety of urban levels.

scholarly journals A Branching Process Model of Evolutionary Rescue

2021 ◽  
Author(s):  
Peter Olofsson ◽  
Ricardo B. R. Azevedo
Keyword(s):  
Population Growth ◽  
Mutation Rate ◽  
Discrete Time ◽  
Growth Curve ◽  
Process Model ◽  
Branching Process ◽  
Selective Advantage ◽  
Population Declines ◽  
Beneficial Mutations ◽  
Evolutionary Rescue

Evolutionary rescue is the process whereby a declining population may start growing again, thus avoiding extinction, via an increase in the frequency of beneficial genotypes. These genotypes may either already be present in the population in small numbers, or arise by mutation as the population declines. We present a simple two-type discrete-time branching process model and use it to obtain results such as the probability of rescue, the shape of the population growth curve of a rescued population, and the time until the first rescuing mutation occurs. Comparisons are made to existing results in the literature in cases where both the mutation rate and the selective advantage of the beneficial mutations are small.

Immigration could sway next Australian election

2018 ◽  
Keyword(s):  
International Trade ◽  
Population Growth ◽  
Public Services ◽  
Growth Strategy ◽  
Economic Downturn ◽  
Content Type ◽  
Net Migration ◽  
Trade War ◽  
Skills Shortages ◽  
Over Time

Subject Immigration in Australia. Significance Support is growing for a lower immigration intake, to reduce pressure on employment and public services -- net migration grew by about 15% in 2017 and accounted for 60% of Australia’s overall population growth. If immigration numbers were reduced, this could reverse a growth strategy that has been in use in the country for about 70 years. Impacts Businesses will encourage the Liberal-led government not to cut immigration numbers. Tighter immigration controls could cause skills shortages over time. An economic downturn, perhaps if there is an international trade war, could see Australian immigration concerns grow.

scholarly journals Mild traumatic brain injury recovery: a growth curve modelling analysis over 2 years

2020 ◽  
Vol 267 (11) ◽  
pp. 3223-3234 ◽  
Author(s):  
Ellen L. Carroll ◽  
Joanne G. Outtrim ◽  
Faye Forsyth ◽  
Anne E. Manktelow ◽  
Peter J. A. Hutchinson ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Growth Curve ◽  
Well Being ◽  
Longitudinal Assessment ◽  
Major Trauma Centre ◽  
Over Time

Abstract Background An improved understanding of the trajectory of recovery after mild traumatic brain injury is important to be able to understand individual patient outcomes, for longitudinal patient care and to aid the design of clinical trials. Objective To explore changes in health, well-being and cognition over the 2 years following mTBI using latent growth curve (LGC) modelling. Methods Sixty-one adults with mTBI presenting to a UK Major Trauma Centre completed comprehensive longitudinal assessment at up to five time points after injury: 2 weeks, 3 months, 6 months, 1 year and 2 years. Results Persisting problems were seen with neurological symptoms, cognitive issues and poor quality of life measures including 28% reporting incomplete recovery on the Glasgow Outcome Score Extended at 2 years. Harmful drinking, depression, psychological distress, disability, episodic memory and working memory did not improve significantly over the 2 years following injury. For other measures, including the Rivermead Post-Concussion Symptoms and Quality of Life after Brain Injury (QOLIBRI), LGC analysis revealed significant improvement over time with recovery tending to plateau at 3–6 months. Interpretation Significant impairment may persist as late as 2 years after mTBI despite some recovery over time. Longitudinal analyses which make use of all available data indicate that recovery from mTBI occurs over a longer timescale than is commonly believed. These findings point to the need for long-term management of mTBI targeting individuals with persisting impairment.

Investigating land use and land cover changes in Dublin, Ireland using Satellite Imagery: A comparative analysis

2020 ◽  
Author(s):  
Bidroha Basu ◽  
Arunima Sarkar Basu ◽  
Srikanta Sannigrahi ◽  
Francesco Pilla
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Population Growth ◽  
Satellite Imagery ◽  
Rainfall Runoff ◽  
Lulc Changes ◽  
The Past ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Over Time

<p>Over the past few decades, there has been over increasing pressure on land due to population growth, urbanization, agriculture expansion and industrialization. The change in land use and land cover (LULC) pattern are highly dependent on human intervention. Deforestation pattern has started due to growth of suburbs, cities, and industrial land. The alarming rate in change of LULC pattern was on a rising trend since 1990s and has been increasing over time. This study focuses on analyzing the changes in LULC pattern in Dublin, Ireland over the past two decades using remotely sensed LANDSAT satellite imagery data, and quantify the effect of LULC change in streamflow simulation in watershed at Dublin by using rainfall-runoff model. Benefit of using remotely sensed image to investigate LULC changes include availability of high-resolution spatial data at free of cost, images captured at high temporal resolution to monitor the changes in LULC during both seasonal and yearly timescale and readily availability of data. The potential classification of landforms has been done by performing both supervised as well as unsupervised classification. The results obtained from the classified images have been compared to google earth images to understand the accuracy of the image classification. The change in LULC can be characterized by changes in building density and urban/artificial area (build up areas increase due to population growth), changes in vegetation area as well as vegetation health, changes in waterbodies and barren land. Furthermore, a set of indices such as vegetation index, building index, water index and drought index were estimated, and their changes were monitored over time. Results of this analysis can be used to understand the driving factors affecting the changes in LULC and to develop mathematical models to predict future changes in landforms. Soil Water Assessment Tool (SWAT) based rainfall-runoff model were used to simulate the changes in runoff due to the LULC changes in watershed over two decades. The developed framework is highly replicable because of the used LANDSAT data and can be applied to generate essential information for conservation and management of green/forest lands, as well as changes in water availability and water stress in the assessed area.</p>

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