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Aurelio José Figueredo

Other affiliations: University of Western Ontario
Bio: Aurelio José Figueredo is an academic researcher from University of Arizona. The author has contributed to research in topics: Personality & Life history theory. The author has an hindex of 51, co-authored 233 publications receiving 12109 citations. Previous affiliations of Aurelio José Figueredo include University of Western Ontario.


Papers
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Journal ArticleDOI
TL;DR: This review demonstrates the value of applying a multilevel evolutionary-developmental approach to the analysis of a central feature of human phenotypic variation: LH strategy, and converging lines of evidence support core assumptions of the theory.
Abstract: The current paper synthesizes theory and data from the field of life history (LH) evolution to advance a new developmental theory of variation in human LH strategies. The theory posits that clusters of correlated LH traits (e.g., timing of puberty, age at sexual debut and first birth, parental investment strategies) lie on a slow-to-fast continuum; that harshness (externally caused levels of morbidity-mortality) and unpredictability (spatial-temporal variation in harshness) are the most fundamental environmental influences on the evolution and development of LH strategies; and that these influences depend on population densities and related levels of intraspecific competition and resource scarcity, on age schedules of mortality, on the sensitivity of morbidity-mortality to the organism’s resource-allocation decisions, and on the extent to which environmental fluctuations affect individuals versus populations over short versus long timescales. These interrelated factors operate at evolutionary and developmental levels and should be distinguished because they exert distinctive effects on LH traits and are hierarchically operative in terms of primacy of influence. Although converging lines of evidence support core assumptions of the theory, many questions remain unanswered. This review demonstrates the value of applying a multilevel evolutionary-developmental approach to the analysis of a central feature of human phenotypic variation: LH strategy.

1,027 citations

Book
27 Mar 2007
TL;DR: This chapter discusses the concept of Missing Data, the current classification system, and some of the methods used in the selection of data Analytic Procedures for handling Missing Data.
Abstract: Part 1. A Gentle Introduction to Missing Data. The Concept of Missing Data. The Prevalence of Missing Data. Why Data Might Be Missing. The Impact of Missing Data. What's Missing in the Missing Data Literature? A Cost-Benefit Approach to Missing Data. Missing Data - Not Just for Statisticians Anymore. Part 2. Consequences of Missing Data. Three General Consequences of Missing Data. Consequences of Missing Data on Construct Validity. Consequences of Missing Data on Internal Validity. Consequences on Causal Generalization. Summary. Part 3. Classifying Missing Data. "The Silence That Betokens". The Current Classification System: Mechanisms of Missing Data. Expanding the Classification System. Summary. Part 4. Preventing Missing Data by Design. Overall Study Design. Characteristics of the Target Population and the Sample. Data Collection and Measurement. Treatment Implementation. Data Entry Process. Summary. Part 5. Diagnostic Procedures. Traditional Diagnostics. Dummy Coding Missing Data. Numerical Diagnostic Procedures. Graphical Diagnostic Procedures. Summary. Part 6. The Selection of Data Analytic Procedures. Preliminary Steps. Decision Making. Summary. Part 7. Data Deletion Methods for Handling Missing Data. Data Sets. Complete Case Method. Available Case Method. Available Item Method. Individual Growth Curve Analysis. Multisample Analyses. Summary. Part 8. Data Augmentation Procedures. Model-Based Procedures. Markov Chain Monte Carlo. Adjustment Methods. Summary. Part 9. Single Imputation Procedures. Constant Replacement Methods. Random Value Imputation. Nonrandom Value Imputation: Single Condition. Nonrandom Value Imputation: Multiple Conditions. Summary. Part 10. Multiple Imputation. The MI Process. Summary. Part 11. Reporting Missing Data and Results. APA Task Force Recommendations. Missing Data and Study Stages. TFSI Recommendations and Missing Data. Reporting Format. Summary. Part 12. Epilogue.

721 citations

Journal ArticleDOI
TL;DR: An integrated theory of individual diVerences that traces the behavioral development of life history from genes to brain to reproductive strategy and applies Life History Theory to predict patterns of development within the brain that are paedomorphic and peramorphic.

602 citations

Journal ArticleDOI
TL;DR: It was found that different forms of abuse in the home were highly interrelated and that children of battered women were at risk for child abuse and there was low agreement on symptoms of child psychopathology.
Abstract: This study examines the link between different forms of family aggression and children's symptoms of psychopathology. The goal of the study was to understand what forms children's problems might take in violent homes and whether close ties within the family (to the mother or a sibling) buffered children. Interviews with 365 mothers and 1 of their children between the ages of 6 and 12 about abuse in the home, support and closeness within the nuclear family, and mother's and children's mental health formed the basis of this study. Families were recruited from battered women's shelters and the community. We found that different forms of abuse in the home were highly interrelated and that children of battered women were at risk for child abuse. Domestic violence predicted children's general psychopathology, but we uncovered little evidence for the presence of specific sorts of disorders as a result of family dysfunction. Although mothers experiencing conjugal violence were more likely to have mental health problems, their mental health did not mediate the children's response to family conflict. Finally, there was less sibling and parental warmth in families marked by aggression, although when it was present, family social support failed to buffer children. Although the general pattern of results was consistent across respondents (mother and child), there was low agreement on symptoms of child psychopathology.

574 citations

Journal ArticleDOI
TL;DR: The evolutionary model contends that understanding the evolutionary functions of adolescence is critical to explaining why adolescents engage in risky behavior and that successful intervention depends on working with, instead of against, adolescent goals and motivations.
Abstract: This article proposes an evolutionary model of risky behavior in adolescence and contrasts it with the prevailing developmental psychopathology model. The evolutionary model contends that understanding the evolutionary functions of adolescence is critical to explaining why adolescents engage in risky behavior and that successful intervention depends on working with, instead of against, adolescent goals and motivations. The current article articulates 5 key evolutionary insights into risky adolescent behavior: (a) The adolescent transition is an inflection point in development of social status and reproductive trajectories; (b) interventions need to address the adaptive functions of risky and aggressive behaviors like bullying; (c) risky adolescent behavior adaptively calibrates over development to match both harsh and unpredictable environmental conditions; (d) understanding evolved sex differences is critical for understanding the psychology of risky behavior; and (e) mismatches between current and past environments can dysregulate adolescent behavior, as demonstrated by age-segregated social groupings. The evolutionary model has broad implications for designing interventions for high-risk youth and suggests new directions for research that have not been forthcoming from other perspectives.

554 citations


Cited by
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[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

14,171 citations

Journal ArticleDOI
TL;DR: Reading a book as this basics of qualitative research grounded theory procedures and techniques and other references can enrich your life quality.

13,415 citations

Journal ArticleDOI
TL;DR: For example, this article found a strong relationship between the breadth of exposure to abuse or household dysfunction during childhood and multiple risk factors for several of the leading causes of death in adults.

12,712 citations

Journal Article
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

9,847 citations