Models of Quantitative Sociology

nauki socjologiczne

średnio-zaawansowany

wpisz symbol/symbole efektów kształcenia:

S2A_W05 S2A_U01, S2A_U02, S2A_U04 S2A_K02

basic statistics

I. THE MAIN ATTRIBUTES OF CONTEMPORARY SOCIAL RESEARCH

II. MODELS OF SOCIAL RESEARCH

III. MODELS OF SOCIAL DATA: DESCRIPTIVE (EXPLORATORY) & INFERENTIAL (EXPLANATORY)

IV. MODELS Of SOCIAL DATA - contin.

V. MODELS OF SOCIAL DATA - cont

VI. MODELS FOR LATENT VARIABLES

VII. CAUSAL MODELLING IN SOCIAL RESEARCH - MODELLING CAUSAL RELATIONSHIP

VIII. TYPES OF CAUSAL MODELS IN SOCIAL RESEARCH

IX . MULTIVARIATE METHODS OF ANALYSIS - an overview

X. LOGIC OF DYNAMIC ANALYSIS

XI. SPATIAL CONTEXT IN SOCIAL RESEARCH

XII. EVALUATION RESEARCH

I. THE MAIN ATTRIBUTES OF CONTEMPORARY SOCIAL RESEARCH: QUALITY – INTERDISCIPLINARITY – UTILITY

II. MODELS OF SOCIAL RESEARCH:

Types of sociological investigations

Units & Levels of Analysis

The Micro-Macro Link

Contemporary Empirical Sociology /CES

Variables and Mechanisms in “empirical quantitative sociology”/EQS

III. MODELS OF SOCIAL DATA: DESCRIPTIVE (EXPLORATORY) & INFERENTIAL (EXPLANATORY)

Goals of Analytical Data Processing / Modelling

-Summarization of data – description, exploration

-Generalization /inference

IV. MODELS Of SOCIAL DATA - contin.

Descriptive Models:

Cluster Analysis (CA)

Multidimensional Scaling (MS)

Correspondence Analysis (CORA)

Principal Component Analysis (PCA)

V. MODELS OF SOCIAL DATA - cont

Model-based Methods:

Factor Analysis (FA)

FA for Binary Data

Latent Class Analysis (LCA) for Binary Data

VI. MODELS FOR LATENT VARIABLES

Latent Class Analysis (LCA)

Classic models for latent class

Typology of latent class models

Models of latent classes for binary data / variables

Latent Class Analysis

& Cluster Analysis

& Latent Profile Analysis

- comparisons

VII. CAUSAL MODELLING IN SOCIAL RESEARCH - MODELLING CAUSAL RELATIONSHIP

- Logic of Causal Analysis

-- Single-factor causes

-- Multi-sources /-factor causality

-- Moderate effects

VIII. TYPES OF CAUSAL MODELS IN SOCIAL RESEARCH

Functional models of causality

--Logic of structural equation

--Counterfactual assumptions in causal modeling

-Causality-based Concepts vs statistical concepts

Causality and structural equation models in social and economic sciences

IX . MULTIVARIATE METHODS OF ANALYSIS - an overview

Multiple Regression

- spatial regression

Logistic Regression

Loglinear Analysis

Discriminant Analysis

Path Analysis

ANOVA /Analysis of Variance

X. LOGIC OF DYNAMIC ANALYSIS

Elements of Survival Analysis & Models of Growth & Progress

Longitudinal Analysis

Panel Data - Panel Dynamic Analysis

Latent Variables Analysis

XI. SPATIAL CONTEXT IN SOCIAL RESEARCH

Spatial Concepts and Spatial Data

- making data spatial /contextualization

- linking survey data (also to GIS)

Spatial Concepts in Social and Statistical Analysis

 Exploratory Spatial Data Analysis /ESDA

Application of Spatial Analysis to Geo-spatial Sociology

 Hierarchical Linear Modelling (HLM)

XII. EVALUATION RESEARCH

Evaluation of Process and Evaluation of Outcome

 Impact Analysis - Social Impact Analysis (SIA)

 Propensity Score Matching Method (PSM)

Pertti ALASUUTARI, Leonard BICKMAN, Julia BRANNEN (eds), 2008. The SAGE Handbook of SOCIAL RESEARCH METHODS. SAGE Publications.

Luc ANSELIN, Jacqueline Cohen, David Cook, Wilpen Gorr, and George Tita. 2000. Spatial Analyses of Crime. Criminal Justice, 2000

David J. BARTHOLOMEW, Fiona STEELE, Irini, MOUSTAKI, Jane I. Galbtaith, 2002. THE ANALYSIS AND INTERPRETATION OF MULTIVARIATE DATA FOR SOCIAL SCIENTISTS. Chapman & Hall/CRC Press Co.

Michael BORENSTEIN, Larry V. HEDGES, Julian P. T. HIGGINS, Hannah R. ROTHSTEIN, 2009. Introduction to Meta-Analysis, J Wiley ans Sons, N.Y.

J. W. CRESWELL, 2003. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (2nd ed.). Thousand Oaks, CA: Sage

Jon ELSTER, 1989. Social Norms and Economic Theory. Journal of Economic Perspectives 3: 99-117.

David KAPLAN (ed.),2004. The SAGE Handbook of Quantitative Methodology for the Social Sciences. SAGE Publications

Andrea MENNICKEN · Robert SALAIS (Eds), 2022. The New Politics of Numbers Utopia, Evidence and Democracy. Palgrave Macmillan,

Włodzimierz OKRASA, 2020. Sociological Aspects of Statistical Research Process: Towards a Sociology of Public Statistics. Polish Sociological Review.Nr.3 (211), 2020.

Włodzimierz OKRASA, 2012a. Statistics and Sociology: The mutually-supportive development from the perspective of interdisciplinarisation of social research, Statistics in Transition new series, Journal of Polish Statistical Association, Vol. 13, Nr 2.

Włodzimierz OKRASA, 2012b. Spatially Integrated Social Research and Official Statistics: Methodological remarks and empirical results on local development, Comparative Economic Research. Central and Eastern Europe,  Wydawnictwo Uniwersytetu Łódzkiego,  4 / 2012 vol. 15.

Karl-Dieter OPP, 2013. What is Analytical Sociology? Strengths and weaknesses of a new sociological research program. Social Science Information (2013) 52: 329 DOI: 10.1177/0539018413483939

William OUTHWAITE, Stephen P. TYURNER (eds), 2007. The SAGE Handbook of SOCIAL SCIENCE METHODOLOGY. SAGE Publications.

Judea PEARL, 2009. CAUSALITY. Models, Reasoning, and Inference. (sec ed.) Cambridge Univ. Press.

Randall E. SCHUMACKER, Richard G. LOMAX, 2010, A Beginner’s Guide to Structural Equation Modeling, 3rd ed., Routledge, NY.

Carsten SCHWEMMER, Oliver WIECZOREK, 2020. The Methodological Divide of Sociology: Evidence from Two Decades of Journal Publications. Sociology (2020), Vol. 54(1) 3–21.

Roger A. STRAUS, 2002. Using Sociology. 3rd Ed., Rowman & Liitlefield Publ. Inc.,Lanham, MD.

Learning outcome no. 1: The student knows and understands the basic concepts of the subject

- the grade 2: The student is not able to name the basic concepts of the subject

- the grade of 3: The student lists, but does not explain the basic concepts

- the grade 4: The student lists and defines the terms incompletely

- the grade 5: The student lists and defines the terms exhaustively

Learning outcome no. 2: The student has in-depth knowledge of the models of sociological analyzes

- to be marked 2: The student is not able to present any methods of analysis

- with a grade of 3: The student lists, but does not characterize, methods of analysis

- with the grade 4: the student lists and characterizes incompletely

- to mark: 5 The student lists the methods of analysis and characterizes them fully

Learning outcome no. 3: The student is able to correctly interpret and explain social phenomena and mutual relations between social phenomena

- to mark 2 The student is not able to correctly interpret social phenomena

- to mark 3 The student uses the simplest methods (interpreting phenomena)

- to be marked 4 The student uses selected methods but does it incompletely

- to mark 5 The student flawlessly uses the methods of analysis and interpretation of given social phenomena, etc.

Educational effect no. 4: Can use theoretical knowledge to describe and analyze the causes and course of social processes and phenomena (can forecast complex social processes, etc.)

- to mark 2 Does not use theoretical knowledge in practical exercises

- to mark 3 Tries to use basic theoretical knowledge in the simplest practical activities

- to mark 4 Uses theoretical knowledge to describe and analyze the causes, but does it incompletely

- to the mark of 5 Fully correctly analyzes and forecasts complex processes, using theoretical knowledge

Learning outcome no. 5: The student works effectively in a team, is able to properly define priorities, enabling the implementation of the set task.

- with a grade of 2: The student cannot work in a team (only individually)

- with a grade of 3: The student tries to cooperate with the Team (but it is effective cooperation)

- with the grade 4: The student works in the Team, but is not able to fully perform the tasks entrusted to him

- to mark 5: The student actively participates in the work of the Team, is able to define priorities, timely and fully implements the tasks entrusted to him

Participation: 20 %

At-class short presentation: 30 %

Home-take ’semester-project’ paper: 50 %

Assessment based on a term paper prepared throughout the semester, including a presentation and submission of a written short report at the end of the semester.