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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

Creative charting of data

This creative time and data chart helps readers understand the details that explain why a broad concept does not always make sense. Official government reports tell us price inflation is low, but our experience tells us so many things cost so much more like health insurance and medical expenses. And compared to retired folks, working people earn so much more than retirees used to earn for the same job. (See  Marketwatch Story for the chart and related data) . I think this type of chart would be useful when dimensions of a metaconcept change over time. For example, the process from an offense to forgiveness has multiple dimensions of change like avoidance and thoughts of revenge. If multiple measures are taken at different time points, they may be plotted over months or years to demonstrate increases and decreases. In fact, the idea of the "cost" of forgiveness might be worthy of consideration. After all, the Christian concept of forgiveness is analogous

FORGIVENESS - Group Forgiveness Scale GFS

Scale Name: Group Forgiveness Scale (GFS) The Group Forgiveness Scale (GFS) was developed to measure forgiveness of identity-related offenses. Research supports three factors for the 17 items: Avoidance, Revenge, Decision to Forgive. In the article describing its development, the authors focused on problems of race relations in the United States (see Davis et al., 2015, below). The GFS is an adaptation of the Transgression-Related Interpersonal Motivations Scale (TRIM). According to the 2015 article by Don Davis and his research team, 17-items resulted in factor loadings on three distinct subscales: Avoidance, Revenge, and Decision to Forgive. Sample items for each factor are as follows: Avoidance             I am avoiding them. Revenge             I am going to get even. Decision to Forgive             I have decided to forgive them. Reliability Data Reliability values were strong as measured by Cronbach’s alpha (Study 3: Avoidance .96; Revenge .9

Religious and Spiritual Struggles Scale Julie Exline et al.

T he Religious and Spiritual Struggles Scale (RSS) assesses six domains of potential struggles, which people may experience. The RSS is a 26-item measure with strong psychometric support. For a list of the items and more details, see the reference below (Exline, Pargament, Grubbs, & Yali, 2014). Based on Exline et al. (2014) and a general reading of the topic, I define religious/ spiritual (RS) struggles as experiences of personal concern linked to RS beliefs, practices, values, or experiences, which negatively affect thinking, feelings, or behavior, relationships, or health. The Six Domains of Spiritual Struggles Following is a quote from page 208 of the 2014 article, which describes the six domains. I have added bold text to help readers identify each domain. Note, r/s is a common abbreviation for religious/spiritual. The measure assesses six domains of r/s struggle: divine (negative emotion centered on beliefs about God or a perceived relationship with God), demo

Religious Coping: The Brief RCOPE scale

The Brief RCOPE scale is a 14-item measure of religious coping developed and studied by Kenneth Pargament (e.g., 1997) and his colleagues. The scale is based on coping theory applied to religion and aims to help researchers understand one relationship between people and their religion when they experience a stressful life experience. Research supports two dimensions of coping reflected in the RCOPE scale: positive and negative. These two dimensions are the basis for two subscales of the Brief RCOPE labelled accordingly as Positive Religious Coping Subscale (PRC ) and Negative Religious Subscale (NRC ). Positive coping means drawing upon spiritual resources in a way that helps people cope with stressful events. Such people may have a secure relationship with God or a higher power, hold a benevolent worldview, and have positive relationships with religious others. Negative religious coping indicates intrapersonal religious or spiritual struggles . The conflict may be exp

Response set and bias in surveys

Response set  is a tendency to respond similarly to all or many questions such as frequently choosing "somewhat agree" on scale options ranging from "strongly agree" to "strongly disagree." Response bias occurs when respondents deliberately give false responses. There are many forms of response bias. Acquiescence bias occurs when respondents select only positive answers. This is also called "yea-saying." Demand characteristics influence answers to survey items when the respondent attempts to provide answers according to the way they think an ideal participant should respond. Extreme bias occurs when respondents frequently choose the extreme options on survey items such as the "Strongly Agree" and "Strongly Disagree" options. Hostility bias  occurs when respondents feel provoked by items in the survey. Researchers must take care in wording items that may be sensitive. Explanations and instructions might help reduc