A correlation is a statistical indicator of the relationship between variables. Prevents carryover effects of learning and fatigue. Social desirability bias is the tendency for interview participants to give responses that will be viewed favorably by the interviewer or other participants. an abstract idea. You test convergent validity and discriminant validity with correlations to see if results from your test are positively or negatively related to those of other established tests. You need to have face validity, content validity, and criterion validity to achieve construct validity. Random sampling enhances the external validity or generalizability of your results, while random assignment improves the internal validity of your study. There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization. In this way, both methods can ensure that your sample is representative of the target population. A sample is a subset of individuals from a larger population. Reliability and validity are both about how well a method measures something: If you are doing experimental research, you also have to consider the internal and external validity of your experiment. 1.1 Concepts as mental representations. Snowball sampling is best used in the following cases: The reproducibility and replicability of a study can be ensured by writing a transparent, detailed method section and using clear, unambiguous language. A confounding variable is closely related to both the independent and dependent variables in a study. Whats the difference between anonymity and confidentiality? There are two subtypes of construct validity. Whats the difference between action research and a case study? However, it provides less statistical certainty than other methods, such as simple random sampling, because it is difficult to ensure that your clusters properly represent the population as a whole. You can avoid systematic error through careful design of your sampling, data collection, and analysis procedures. To make quantitative observations, you need to use instruments that are capable of measuring the quantity you want to observe. Using careful research design and sampling procedures can help you avoid sampling bias. You can also use regression analyses to assess whether your measure is actually predictive of outcomes that you expect it to predict theoretically. Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down. What are the pros and cons of triangulation? You can mix it up by using simple random sampling, systematic sampling, or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study. Constructs can be conceptually defined in that they have meaning in theoretical terms. Categorical variables are any variables where the data represent groups. What are some types of inductive reasoning? Our concepts don't exist in the real world, so they cannot be measured directly, but we can measure the things our concepts summarize. Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys, and statistical tests). The external validity of a study is the extent to which you can generalize your findings to different groups of people, situations, and measures. It can help you increase your understanding of a given topic. 2.2: Concepts, Constructs, and Variables - Social Sci LibreTexts . These scores are considered to have directionality and even spacing between them. A sampling error is the difference between a population parameter and a sample statistic. What are the main qualitative research approaches? Together, they help you evaluate whether a test measures the concept it was designed to measure. A hypothesis states your predictions about what your research will find. Phenomena. is that concept is an understanding retained in the mind, from experience, reasoning and/or imagination; a generalization (generic, basic form), or abstraction (mental impression), of a particular set of instances or occurrences (specific, though different, recorded manifestations of the concept) while construct is something constructed from parts. These considerations protect the rights of research participants, enhance research validity, and maintain scientific integrity. This means that each unit has an equal chance (i.e., equal probability) of being included in the sample. A dependent variable is what changes as a result of the independent variable manipulation in experiments. There are eight threats to internal validity: history, maturation, instrumentation, testing, selection bias, regression to the mean, social interaction and attrition. What's the difference between concepts, variables, and indicators? In mixed methods research, you use both qualitative and quantitative data collection and analysis methods to answer your research question. This Conceptual research doesn't involve conducting any practical experiments. You avoid interfering or influencing anything in a naturalistic observation. This can lead you to false conclusions (Type I and II errors) about the relationship between the variables youre studying. Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions. Constructs are broad concepts or topics for a study. The two variables are correlated with each other, and theres also a causal link between them. Whats the definition of an independent variable? Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. Whats the difference between exploratory and explanatory research? What is the difference between concepts and construct? In contrast, groups created in stratified sampling are homogeneous, as units share characteristics. Open-ended or long-form questions allow respondents to answer in their own words. Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports). How do I prevent confounding variables from interfering with my research? Data validation at the time of data entry or collection helps you minimize the amount of data cleaning youll need to do. Why are convergent and discriminant validity often evaluated together? In this article, the authors set out to clarify the meaning of these terms and to describe how they are used in 2 approaches to research commonly used in HPE: the objectivist deductive approach (from . Whats the difference between correlation and causation? Such patterns of relationships are called propositions. PDF Distinguishing between Theory, Theoretical Framework, and - ed What is the difference between internal and external validity? The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable. Discriminant validity indicates whether two tests that should, If the research focuses on a sensitive topic (e.g., extramarital affairs), Outcome variables (they represent the outcome you want to measure), Left-hand-side variables (they appear on the left-hand side of a regression equation), Predictor variables (they can be used to predict the value of a dependent variable), Right-hand-side variables (they appear on the right-hand side of a, Impossible to answer with yes or no (questions that start with why or how are often best), Unambiguous, getting straight to the point while still stimulating discussion. Questionnaires can be self-administered or researcher-administered. If participants know whether they are in a control or treatment group, they may adjust their behavior in ways that affect the outcome that researchers are trying to measure. Correlation describes an association between variables: when one variable changes, so does the other. A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. In a longer or more complex research project, such as a thesis or dissertation, you will probably include a methodology section, where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods. You are seeking descriptive data, and are ready to ask questions that will deepen and contextualize your initial thoughts and hypotheses. How do you randomly assign participants to groups? The 4 Types of Validity in Research | Definitions & Examples - Scribbr Take your time formulating strong questions, paying special attention to phrasing. Cross-sectional studies cannot establish a cause-and-effect relationship or analyze behavior over a period of time. If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variables, or even find a causal relationship where none exists. Once divided, each subgroup is randomly sampled using another probability sampling method. That way, you can isolate the control variables effects from the relationship between the variables of interest. What is the difference between discrete and continuous variables? Whats the difference between clean and dirty data? Definition of Concept Here is a standard textbook definition of the term, taken from LeRoy and Corbet, Research Methods in Political Science (Belmont, California: Wadsworth Thompson, 2006, p.25). Basically, if evidence accumulates to support a hypothesis, then the hypothesis can become accepted as a good explanation of a . What are the pros and cons of a between-subjects design? In inductive research, you start by making observations or gathering data. The ontology of concepts. Dirty data can come from any part of the research process, including poor research design, inappropriate measurement materials, or flawed data entry. by arranging words or ideas. A systematic review is secondary research because it uses existing research. While these ideas are directly connected, they also have unique applications. Measure more than once. However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied. Concepts - Stanford Encyclopedia of Philosophy This section often confuses students because the three ideas seem to overlap. To implement random assignment, assign a unique number to every member of your studys sample. The validity of your experiment depends on your experimental design. If there are ethical, logistical, or practical concerns that prevent you from conducting a traditional experiment, an observational study may be a good choice. A regression analysis that supports your expectations strengthens your claim of construct validity. For example, if you were stratifying by location with three subgroups (urban, rural, or suburban) and marital status with five subgroups (single, divorced, widowed, married, or partnered), you would have 3 x 5 = 15 subgroups. When its taken into account, the statistical correlation between the independent and dependent variables is higher than when it isnt considered. Within-subjects designs have many potential threats to internal validity, but they are also very statistically powerful. When should I use a quasi-experimental design? What are the main types of research design? The multistore model of human memory efficiently summarizes many important phenomena: the limited capacity and short retention time of information that is attended to but not rehearsed, the importance of rehearsing information for long-term retention, the serial-position effect, and so on. the methodological aspects of the study with these questions. This means that you cannot use inferential statistics and make generalizationsoften the goal of quantitative research. For a probability sample, you have to conduct probability sampling at every stage. You have prior interview experience. This includes rankings (e.g. In research, you might have come across something called the hypothetico-deductive method. But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples. Clean data are valid, accurate, complete, consistent, unique, and uniform. Individual differences may be an alternative explanation for results. For clean data, you should start by designing measures that collect valid data. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. If you test two variables, each level of one independent variable is combined with each level of the other independent variable to create different conditions. Samples are used to make inferences about populations. A measure with high construct validity accurately reflects the abstract concept that the researcher wants to study. Constructs are considered latent variable because they cannot be directly observable or measured. For example, use triangulation to measure your variables using multiple methods; regularly calibrate instruments or procedures; use random sampling and random assignment; and apply masking (blinding) where possible. Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. How can you ensure reproducibility and replicability? You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals. What are independent and dependent variables? The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment. For some research projects, you might have to write several hypotheses that address different aspects of your research question. What is the difference between quantitative and categorical variables? A scientific theory summarizes a hypothesis or group of hypotheses that have been supported with repeated testing. Can you use a between- and within-subjects design in the same study? Reproducibility and replicability are related terms. Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. To find the slope of the line, youll need to perform a regression analysis. : Using different methodologies to approach the same topic. Naturalistic observation is a qualitative research method where you record the behaviors of your research subjects in real world settings. Whats the difference between a statistic and a parameter? As a rule of thumb, questions related to thoughts, beliefs, and feelings work well in focus groups. Overall, your focus group questions should be: A structured interview is a data collection method that relies on asking questions in a set order to collect data on a topic. Are Likert scales ordinal or interval scales? Action research is particularly popular with educators as a form of systematic inquiry because it prioritizes reflection and bridges the gap between theory and practice. Whats the difference between closed-ended and open-ended questions? Random and systematic error are two types of measurement error. Each of these is a separate independent variable. Chapter 6 Measurement of Constructs. You can only guarantee anonymity by not collecting any personally identifying informationfor example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos. Lastly, the edited manuscript is sent back to the author. What are the types of extraneous variables? Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable. Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors. Yes, but including more than one of either type requires multiple research questions.