Study Guide Chapters 1,3,4,5,6 PDF

Chapter 1: Human Inquiry and Science 1. Why is it important to have a strong understanding of research methods… even if you don’t want to do research? Can help you become a more critical consumer of research evidence, so that you can: Read and understand research reports and articles Know what quest...

Chapter 1: Human Inquiry and Science 1. Why is it important to have a strong understanding of research methods… even if you don’t want to do research? Can help you become a more critical consumer of research evidence, so that you can: Read and understand research reports and articles Know what questions to ask to evaluate the quality of information Determine whether information is credible Can help you become an active producer of research evidence, so that you can: Conduct your own research as student Do research in your post-graduate career 2. What is the general research process? Start of by Considering Theory/ Review Literature 1. Formulate Research Question (reading research that others have done that relate to this whether it was successful or not successful) 2. Prepare Research Design (assess research ethics, develop measures, select sample) - (sample could be rare - not representative of a larger population) 3. Collect Data (Ex: experiments, surveys, existing data analysis, multiple methods) 4. Analyze and Interpret Data (Ex: qualitative and quantitative data) 3. Four basic approaches to social research 1. Experiments = Controlled interventions and observations Advantages Involve causation and manipulation of variables Ideal for understanding the causes of human behavior Limitations Limited to what can be manipulated Often raise questions of ethics What are some questions we could answer with an experiment? Effectiveness of a drug (could also be compared to another drug) 2. Surveys (Questionnaires or interviews) Advantages (can get more people to answer than experiment) Involve asking questions of a relatively large randomly selected group of people Yield precise statistical estimates of group characteristics Limitations Respondents may not be truthful What people say may not predict what they do Could be based of people’s percepton (can leave room for many interpretations) What are some questions we could answer with surveys? Estimates of root characteristics maybe (Would you vote for blah blah) How often do you walk? (Often, rarely, sometimes, etc …) 3. Field Research (Direct observations and in-depth interviews) Advantages Involves observing people in natural settings and/or interviewing them in depth Provides rich information on social meanings and processes Limitations Often difficult to know the generalizability of research results Why = Qualitative (processes of why people think that????) (How much of what we found can be applied to a larger population?) 4. Analysis of Existing data (Analyzing data from existing sources) Advantages: Involves the analysis of data not produced directly by the researcher who uses them Well suited to studying the past and social change Data often are unobtrusive Limitations May be difficult to find data that can adequately address the research question Existing data (Using surveys or other info available to help form an understanding of how something has changed over time or if it’s still relevant) Differences between approaches Experiments: Focus on causation and manipulation of variables. Surveys: Aim to gather information from a large and representative sample. Field Research: Emphasizes understanding social meanings and behaviors in natural settings. Analysis of Existing Data: Involves studying data not directly collected by the researchers. How do you determine which is best? Ultimately, researchers may use a combination of approaches or choose the one that best fits the specific requirements of their study. Chapter 3: The Ethics of Social Research 1. What are research ethics? Research ethics = ethical standards applied to conducting research - Whether the researchers are being ethical (in doing it correctly, reporting things accurately, etc...) 2. What is the purpose of research ethics? Research ethics help guide the proper treatment of human subjects and scientific integrity in studies. 3. Are there any disadvantages to research ethics? Ethical standards evolve, are not always clear cut, may be context dependent, and are subject to interpretation. 4. Know the 4 main considerations of research ethics 1. Potential harm = The principle that individuals should be given enough info about a study to make an informed decision about participation. Harm may be physical or psychological. Level of risk to participants Risks of the research in relation to the benefits Risk vs benefit - Who benefits? - Assessment of Risks and Benefits 2. Informed consent = The principle that individuals should be given enough info about a study to make an informed decision about participation. Arises from the value placed on freedom of choice. 9 key parts 1. statement that the study involves research 2. explanation of the purpose of the research 3. expected duration of the participants participation 4. description of the procedures to be followed 5. description of risks 6. description of any benefits to the participant or to others 7. statement describing the confidentiality of records 8. explanation of who to contact pertaining to questions about the research/participation procedures, rights and who to contact if a research related injury occurs 9. statement that participation is voluntary and refusal to participate will not result in any penalty or loss of benefits to which the participant is entitled (they can quit at any time) 3. Deception = Intentionally misleading participants about a study (Usage is controversial). Examples: Federal Regulations Professional Regulations Exceptions Exceptions and requirements May be allowed in research when there are no effective alternatives and steps are taken to minimize harm. Debriefing afterwards is essential to inform participants about the deception and true purpose. Debriefing = a session at the end of a study in which an investigator meets with a participant to impart information about the study, including the real purpose and the nature/purpose of deception (if used), and to respond to questions and concerns. 4. Invasion of privacy = individuals have the right to decide when and to what extent personal info is revealed. Participant protection methods Anonymity = ethical safeguard against invasion of privacy in which data cannot be identified with particular research participants Confidentiality = the ethical safeguard against invasion of privacy by which data obtained from participants are not shared with others without their permission 5. Be familiar with lecture examples of when these considerations were potentially violated “No harm” example = Medical experimentation on prisoners of war by Nazi researchers in World War II “Informed consent” example = Facebook experiments of 2012 using “big data” that are created by the millions and millions of internet actions. The reachers wanted to see how their subscribers were affected by positive or negative info they received on there pages (Were not told any of this info - basically used as guinea pigs to prove their theory) “Privacy and anonymity” example = Exxon supertanker had spilled 10 million gallons of oil into the bay (in Alaska). While there was economic and environmental damage reported. Researchers interviewed the 22 communities affected by this (in a survey), Exxon forced them to testify in court (even though they were all supposed to remain anonymous) 6. Be familiar with Belmont Report, Common Rule, and Professional ethical guidelines Belmont Report (1979) 1. Respect for persons = participation must be completely voluntary and have complete knowledge of what’s involved (Special caution taken to protect minors and prisoners) 2. Beneficience = subjects must not be harmed by the researcher and, ideally, should benefit from it. 3. Justice = the burdens and benefits of research should be shared fairly within the society Common Rule (1991) - Established federal policy for the protection of human subjects in research - Applies to every college university Professional ethical guidelines = most professional associations of social researchers have created and published formal codes of conduct describing what is considered acceptable and unacceptable professional behavior. (Ex: American Association for public Opinion Research (AAPOR)) 7. What is the IRB? What do they do? Institutional Review Board (IRB) = A committee formed at nearly all colleges and universities review research proposals to assess the treatment of human (and animal) subjects judge if theres appropriate safeguards for the ethical treatment of participants approve modify or reject proposals 8. Political influence on research Personal Personal values and political ideology Structural Groups, professional organizations, and political systems at all levels 9. What is the Role/issues with private funding Politics of research funding Most social research requires financial support Sources of support prioritize particular topics Coburn amendment to 2013 spending bill is an example 10. What are ethical considerations related to data analysis? Data analysis issues = In operationalization, data cleaning, model specification, and statistical analysis, there are many choices researchers make that can potentially influence results Interpretation issues = Researchers may consciously or unconsciously interpret findings in a way aligned with personal views or interests. Dissemination issues = Researchers must consider how to responsibly share findings, including dealing with misrepresentation and speaking out when necessary 11. What is conflict of interest? Conflict of interest: Conflict between the goal of producing unbiased knowledge and other motives such as financial gain and political interests Regnerus study supported by foundations opposed to same-sex marriage Chapter 4: Research Design 1. Components of a good research question? Interesting because it contributes to ongoing research and theory Focused by being specific and concrete Manageable or feasible in terms of time and other resources 2. Quant vs Qual research questions Quantitative research questions Asks about relationships between variables The systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques. Qualitative research questions Asks about social processes and the meaning and cultural significance of phenomena Refers to the meanings, concepts definitions, characteristics, metaphors, symbols, and description of things" and not to their "counts or measures Considerations for quant data collections 3. Know the different types of variables Variable = a measured concept that varies over cases or over time within a given case Types of variables: Dependent Independent 4. How do we assess relationships between variables in quantitative studies? Correlation = Are changes in one variable accompanied by systematic changes in another? Tests of statistical significance determine whether an association could have occurred by chance Direction of influence = Which variable in an association influences changes in the order. Usually determined by temporal order Makes the timing of an observation an important element of the research design 5. What is a spurious relationship? Spurious relationship = a non-causal statistical association between two variables produced by a common cause (Ex: high correlation between palm trees and retirees) 6. Research strategies for qualitative data collections Which research strategies generally address qualitative questions? Field research In-depth interviews Some forms of existing data analysis Selecting Cases in qualitative research Generally select a single setting or small number of cases Should fit the question May depend on the ability to gain access Based on how much cases will enhance theoretical understanding 7. Inductive vs deductive logic of inquiry Deductive Logic = Deductive reasoning starts with a general statement or hypothesis and examines the possibilities to reach a specific, logical conclusion. ​Deductive Logic Example: Premise 1: All cats have tails. Premise 2: Fluffy is a cat. Conclusion: Therefore, Fluffy has a tail. In this case, the deductive reasoning starts with the general statement (all cats have tails) and applies it to a specific case (Fluffy), leading to the logical conclusion that Fluffy must have a tail. Inductive Logic = Inductive reasoning begins with specific observations or evidence and works towards a broader, generalized conclusion. (EX: The sun has risen every day in the past. Therefore, the sun will rise tomorrow.) Chapter 5: Conceptualization, Operationalization, & Measurement 1. What is measurement? Measurement = The process of assigning numbers or labels to represent conceptual properties Generally follows the deductive model of inquiry, moving from abstract concepts to specific, concrete ways of observing them 2. Be able to outline the measurement process (figure in slide 4) 3. Conceptualization: Definition/Purpose/Importance Conceptualization = The process through which we specify what we mean when we use particular terms in research. Objective = is to clarify the meaning concepts embedded in the research question​​ Clarification may occur by (Process of Clarification) Defining the theoretical meaning of the concept (nominal definition) Distinguishing the concept from similar concepts Identifying indicators Identifying dimensions How? Literature Reviews Cognitive interviews = (give somebody same survey, less concerned about how they answer, and more concerned if the partipant is looking at it in the same way you are) 4. Differences between concepts, indicators, and dimensions (EX: Mental health (CONCEPT), Depression (DIMENSION), Depressive symptoms scales (INDICATORS) 5. Operationalization: what is it, how do you do it? Objective of operationalization is to identify ways of observing variation in the concept Two steps: Identify empirical indicators of the concept - May be based on conceptual dimensions Multiple indicators are preferable to a single indicator (more data points to be had) Spell out procedures for applying indicators in collecting data Consists of indicators + procedures 6. Be familiar with variables and attributes Defining Variables and Attributes An attribute is a characteristic or quality of something (EX: female, old, student) A variable is a logical set of attributes (EX: gender, age). Every variable must have two important qualities. The attributes composing it should be exhaustive. Attributes must be mutually exclusive. Which one of these set of attributes is not mutually exclusive? Let's consider an example with the set of attributes: "current employment status." Attributes: Employed Unemployed Student In this case, the attribute "Student" is not mutually exclusive because an individual can be both employed and a student simultaneously (for example, someone working part-time while attending school). Therefore, the attribute "Student" violates the mutual exclusivity criterion. 7. Levels of measurement (Know the types, characteristics, be able to give examples) Levels of measurement = indicate the conclusions that may be drawn when comparing units to one another Each level has the qualities of the level below it plus some other quality Types: Nominal = Merely labels variable categories (anything nominal can do - ratio, interval, & ordinal can do) Indicate whether two cases are the same or different Categories should be exhaustive and mutually exclusive (EX: hair color, nationalities, religion, marital status = No RANK order) Nominal research methods are used to explore and analyze the distribution of these categories within a population or sample. Ordinal = Numbers indicate Rank order Research Question: What is the perceived satisfaction level of customers regarding a product? Ordinal Variable: Customer Satisfaction Level Ordinal Categories: ​ - Very Dissatisfied ​ - Dissatisfied ​ - Neutral ​ - Satisfied ​ - Very Satisfied Interval: Numbers indicate distances between cases (Temp - measuring the absence or presence of heat (ONLY F & C at 0 (still has heat) - kelvin 0 has true absence of heat) Research Question: What is the average temperature change in different cities over a month? Interval Variable: Temperature Change (measured in degrees Celsius) Interval Research Methods: Temperature Measurements: Use temperature sensors to collect data on the daily temperature changes in various cities. Statistical Analysis: Calculate the mean, standard deviation, and other statistical measures to analyze the central tendency and variability of temperature changes. Comparative Studies: Compare temperature changes between different cities or over different time periods. Ratio = Has an absolute zero point so that different numbers may form a ratio (# of businesses, student - once you hit zero there is a true absence (meaning actually nothing)) - (Ratio can NOT be done by other types) Research Question: What is the fuel efficiency of different car models in miles per gallon (mpg)? Ratio Variable: Fuel Efficiency (measured in miles per gallon) Ratio Research Methods: Direct Measurement: Collect data on the distance traveled and the amount of fuel consumed for each car model. Calculations: Calculate the ratio of miles traveled to gallons of fuel consumed for each car model. Comparative Analysis: Compare the fuel efficiency ratios of different car models to identify patterns or trends. 8. Definition and relationships of reliability and validity What is reliability? Stability or consistency of an operational definition What is measurement validity? Goodness of fit between an operational definition and the concept it is intended to measure What is the relationship between reliability and validity? A reliable measure may or may not be valid An unreliable measure cannot be valid 9. How do we assess reliability and validity RELIABILITY ASSESSMENT Test-retest: Measure the same units or persons on two separate occasions Correlation should be high, at least.80 Often impractical and results may be unclear Internal consistency = Measure the consistency of “scores” across a set of items Applies only to composite measures (i.e., indexes and scales) Cronbach’s alpha is a common statistic Inter-rater = Measure consistency across different observers or coders Applies when observers are coding behavior Applies when raters or coders are coding documents How can you assess Validity? Face Validity = The quality of an indicator that makes it seem a measure of some variable reasonable Criterion-related validity = The degree to which a measure relates to some external criterion Construct validity = degree to which a measure related to other expected within a system of theoretical relationships variables as Content validity = how much a measure covers a range of meanings within a concept Chapter 6: Indexes, Scales and Typologies 1. Why do researchers use composite measures like indexes and scales? No clear, unambiguous single indicators Use ordinal measure Efficient for data analysis 2. What do indexes and scales have in common? Commonalities Both scales and indexes are ordinal measures of variables. Both scales and indexes are composite measures of variables – measurements based on more than one data item. 3. How are indexes and scales different? Differences Index = A type of composite measure that summarizes and rank-orders several specific observations and represents some more general dimensions. Scale = A type of composite measure composed of several items that have a logical or empirical structure among them. 4. What is the logic behind scale and index construction (See examples on slides 5 and 6) 5. What are some key considerations for indexes? 1. Item Selection Face Validity Unidimensionality General or Specific Variance 2. Examination of Empirical Relationships 3. Index Scoring 4. Handling Missing Data 5. Index Validation