Skip to main content


Showing posts from March, 2020

Death and Treatment Need Statistics 2020 Pandemic

Statistical models are needed to guide government leaders and health service providers concerned with maximizing the number of infected people who survive and providing high quality care to those in need. All models have multiple assumptions. In the midst of a pandemic such as Covid-19, new data are constantly being processed. Thus, parameters will need to be changed as new data change the models. Multiple outcomes must be considered without biased interpretations favoring either lower or higher estimates. NYT 13 March 2020 reported by Sheri Fink This report refers to four scenarios and is early than the ones further down the page. "Between 160 million and 214 million people in the United States could be infected over the course of the epidemic, according to a projection that encompasses the range of the four scenarios. That could last months or even over a year, with infections concentrated in shorter periods, staggered across time in different communities

Watch those Covid 19 curves

Some highly intelligent scientists have used available data to plot trends related to the spread of Covid-19 such as number of identified infections, recoveries, and deaths. Others plotted ideas rather than data such as flattening the curve. Some rely on "common sense" and others rely on data. Given my experience in teaching graduate research methods and statistics and talking with physicians and psychologists about statistics, I think it worth reminding any readers of this post that a lot of very intelligent people have difficulty with statistical models. There are many PhDs younger than I who know more methods of sophisticated data analyses than I learned during my PhD or since; however, not everyone stops to consider their assumptions when modeling data. That's my point here--we need to review and challenge the assumptions about the data, the way the data are plotted, and how people interpret those data. Missing data are very important to developing an accurat

Life expectancy and lifespan assessment in psychology

Lifespan is not the same concept as life expectancy. Lifespan is the maximum period of time a species lives. The human lifespan is measured in years. As of 2020, the documented human lifespan is 122 years ( see also lifespan concept in psychological science). Life expectancy is the average period of time a member of a population with certain characteristics lives. Human life expectancy, measured in years, varies by sex and environment. Human life expectancy varies by the age group. For example, life expectancy of people at birth will be different from a group of people who are alive at age 70. United Nations data are reported by sex and country. Overall, there has been an increase in human life expectancy on a worldwide basis between 1950 (47.0 years) and 2020 (73.2 years;  worldometers ). I have rounded the numbers which were reported up to two decimal places. Examples of recent life expectancy data for wealthy nations reveal marked differences compared to other nations. Da