The Distinctions Between Theory, Theoretical Framework, and - LWW The directionality problem is when two variables correlate and might actually have a causal relationship, but its impossible to conclude which variable causes changes in the other. Inductive reasoning is also called inductive logic or bottom-up reasoning. In all three types, you first divide the population into clusters, then randomly select clusters for use in your sample. If you dont have construct validity, you may inadvertently measure unrelated or distinct constructs and lose precision in your research. Our concepts don't exist in the real world, so they cannot be measured directly, but we can measure the things our concepts summarize. A correlation reflects the strength and/or direction of the association between two or more variables. 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. Because of this, not every member of the population has an equal chance of being included in the sample, giving rise to sampling bias. A theory is valid as long as there is no evidence to dispute it. In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). A confounding variable is a third variable that influences both the independent and dependent variables. You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Research Methods in Psychology . Can I stratify by multiple characteristics at once? What are the benefits of collecting data? Construct validity is often considered the overarching type of measurement validity. Blinding means hiding who is assigned to the treatment group and who is assigned to the control group in an experiment. Probability sampling means that every member of the target population has a known chance of being included in the sample. Then, you take a broad scan of your data and search for patterns. Prevents carryover effects of learning and fatigue. In quota sampling, you first need to divide your population of interest into subgroups (strata) and estimate their proportions (quota) in the population. A concept is "an abstraction based on characteristics of perceived reality." Wow--that is pretty abstract itself. Snowball sampling relies on the use of referrals. All questions are standardized so that all respondents receive the same questions with identical wording. 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. Random and systematic error are two types of measurement error. What is the difference between quota sampling and convenience sampling? 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. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students. as they are embedded within the research questions. Anonymity means you dont know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. You already have a very clear understanding of your topic. Constructs are considered latent variable because they cannot be directly observable or measured. Define and explain the difference between theory, concept, construct, variable, and model Theory: "a set of interrelated concepts, definitions, and propositions that presents a systematic view of events or situations by specifying relations among variables in order to explain and predict the events of the situations" Decide on your sample size and calculate your interval, You can control and standardize the process for high. The purpose in both cases is to select a representative sample and/or to allow comparisons between subgroups. In research, you might have come across something called the hypothetico-deductive method. In this sense, the con-ceptual framework helps align the analytic tools and methods of a study with the focal topics and . A true experiment (a.k.a. Uses more resources to recruit participants, administer sessions, cover costs, etc. Whats the difference between closed-ended and open-ended questions? A 4th grade math test would have high content validity if it covered all the skills taught in that grade. Random sampling or probability sampling is based on random selection. Whats the difference between random and systematic error? They input the edits, and resubmit it to the editor for publication. What is the difference between criterion validity and construct validity? Neither one alone is sufficient for establishing construct validity. Therefore, theories can be disproven. Whats the definition of an independent variable? What is the difference between random sampling and convenience sampling? Phenomena. You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause, while a dependent variable is the effect. This means that you cannot use inferential statistics and make generalizationsoften the goal of quantitative research. Its a form of academic fraud. The downsides of naturalistic observation include its lack of scientific control, ethical considerations, and potential for bias from observers and subjects. You can also use regression analyses to assess whether your measure is actually predictive of outcomes that you expect it to predict theoretically. 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. Such patterns of relationships are called propositions. You need to have face validity, content validity, and criterion validity to achieve construct validity. This means that each unit has an equal chance (i.e., equal probability) of being included in the sample. brands of cereal), and binary outcomes (e.g. Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. Reproducibility and replicability are related terms. For a probability sample, you have to conduct probability sampling at every stage. Guide 3: Reliability, Validity, Causality, and Experiments Explanatory research is a research method used to investigate how or why something occurs when only a small amount of information is available pertaining to that topic. 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. Categorical variables are any variables where the data represent groups. Sometimes only cross-sectional data is available for analysis; other times your research question may only require a cross-sectional study to answer it. What are the pros and cons of a within-subjects design? Blinding is important to reduce research bias (e.g., observer bias, demand characteristics) and ensure a studys internal validity. There are two subtypes of construct validity. 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). Its usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions. Systematic errors are much more problematic because they can skew your data away from the true value. They might alter their behavior accordingly. If you dont control relevant extraneous variables, they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable. For example, say you want to investigate how income differs based on educational attainment, but you know that this relationship can vary based on race. A. phenomenon. What are the types of extraneous variables? If your response variable is categorical, use a scatterplot or a line graph. concepts. Whats the difference between a mediator and a moderator? Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. Illustrates how research methodology and research method relate to . What is the difference between quota sampling and stratified sampling? However, in convenience sampling, you continue to sample units or cases until you reach the required sample size. It also represents an excellent opportunity to get feedback from renowned experts in your field. If you want data specific to your purposes with control over how it is generated, collect primary data. A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. 1.2 Concepts as abilities. Concepts are constructs; they represent the agreed-on meanings we assign to terms. While a between-subjects design has fewer threats to internal validity, it also requires more participants for high statistical power than a within-subjects design. How do you define an observational study? What is the difference between internal and external validity? This section often confuses students because the three ideas seem to overlap. In a factorial design, multiple independent variables are tested. On the other hand, convenience sampling involves stopping people at random, which means that not everyone has an equal chance of being selected depending on the place, time, or day you are collecting your data. Yes. It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives. After data collection, you can use data standardization and data transformation to clean your data. If there are ethical, logistical, or practical concerns that prevent you from conducting a traditional experiment, an observational study may be a good choice. This allows you to draw valid, trustworthy conclusions. of each question, analyzing whether each one covers the aspects that the test was designed to cover. 2.2: Concepts, Constructs, and Variables - Social Sci LibreTexts Conceptual research is defined as a methodology wherein research is conducted by observing and analyzing already present information on a given topic. Individual Likert-type questions are generally considered ordinal data, because the items have clear rank order, but dont have an even distribution. When its taken into account, the statistical correlation between the independent and dependent variables is higher than when it isnt considered. Further problematizing this situation is the fact that theory, theoretical framework, and conceptual framework are terms that are used in different ways in different research approaches. For example, in an experiment about the effect of nutrients on crop growth: Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design. Naturalistic observation is a qualitative research method where you record the behaviors of your research subjects in real world settings. 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. Phenomenology aims to explain experiences. Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. What are the pros and cons of multistage sampling? In quota sampling you select a predetermined number or proportion of units, in a non-random manner (non-probability sampling). Face validity is about whether a test appears to measure what its supposed to measure. Why do confounding variables matter for my research? How can you ensure reproducibility and replicability? In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources. When should I use a quasi-experimental design? There are seven threats to external validity: selection bias, history, experimenter effect, Hawthorne effect, testing effect, aptitude-treatment and situation effect. They can be abstract and do not necessarily need to be directly observable. They can provide useful insights into a populations characteristics and identify correlations for further research. What is an example of a longitudinal study? What are the requirements for a controlled experiment? Correlation describes an association between variables: when one variable changes, so does the other. Data cleaning involves spotting and resolving potential data inconsistencies or errors to improve your data quality. These are four of the most common mixed methods designs: Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) Dirty data can come from any part of the research process, including poor research design, inappropriate measurement materials, or flawed data entry. A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires. This type of bias can also occur in observations if the participants know theyre being observed. In statistics, dependent variables are also called: An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects.
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