How should I measure it? Some guidelines for the design of clinical trials 2 Collecting data How should I enter and store the data? Data [R]angling — finding a specific observation for an individual using dplyr What program should I use? What type of variable is the outcome variable? How do I look at data with lots of variables?
What is a confidence interval? How can I present my results clearly? What program should I use? Posted on Wednesday 20 May by moniqueb. Which variable is the outcome variable? For a probability sample, you have to probability sampling at every stage. 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.
Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication. Scientists and researchers must always adhere to a certain code of conduct when collecting data from others.
These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity. Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe. Both are important ethical considerations. You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.
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. Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.
Want to contact us directly? No problem. We are always here for you. Scribbr specializes in editing study-related documents. We proofread:. You can find all the citation styles and locales used in the Scribbr Citation Generator in our publicly accessible repository on Github. Frequently asked questions See all. Home Frequently asked questions Can I include more than one independent or dependent variable in a study? Can I include more than one independent or dependent variable in a study?
What is sampling? Reliability and validity are both about how well a method measures something: Reliability refers to the consistency of a measure whether the results can be reproduced under the same conditions.
Validity refers to the accuracy of a measure whether the results really do represent what they are supposed to measure. What is the difference between internal and external validity? What is experimental design? To design a controlled experiment, you need: A testable hypothesis At least one independent variable that can be precisely manipulated At least one dependent variable that can be precisely measured When designing the experiment, you decide: How you will manipulate the variable s How you will control for any potential confounding variables How many subjects or samples will be included in the study How subjects will be assigned to treatment levels Experimental design is essential to the internal and external validity of your experiment.
What are independent and dependent variables? For example, in an experiment about the effect of nutrients on crop growth: The independent variable is the amount of nutrients added to the crop field. The dependent variable is the biomass of the crops at harvest time. What is the difference between quantitative and categorical variables?
What is the difference between discrete and continuous variables? Discrete and continuous variables are two types of quantitative variables : Discrete variables represent counts e. Continuous variables represent measurable amounts e.
What is a confounding variable? How do I decide which research methods to use? If you want to measure something or test a hypothesis , use quantitative methods. If you want to explore ideas, thoughts and meanings, use qualitative methods.
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data. If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.
What is mixed methods research? What is internal validity? What are threats to internal validity? What is the difference between a longitudinal study and a cross-sectional study? What are the pros and cons of a longitudinal study? What is an example of a longitudinal study? How long is a longitudinal study?
Why do a cross-sectional study? What are the disadvantages of a cross-sectional study? What is external validity? What are the two types of external validity?
What are threats to external validity? Why are samples used in research? When are populations used in research? What is sampling error? What is sampling bias? Why is sampling bias important? What are some types of sampling bias? How do you avoid sampling bias? What is probability sampling? What is non-probability sampling? Why are independent and dependent variables important? What is an example of an independent and a dependent variable?
The type of soda — diet or regular — is the independent variable. The level of blood sugar that you measure is the dependent variable — it changes depending on the type of soda. Can a variable be both independent and dependent? Why do confounding variables matter for my research?
What is the difference between confounding variables, independent variables and dependent variables? How do I prevent confounding variables from interfering with my research? What is data collection? What are the benefits of collecting data? When conducting research, collecting original data has significant advantages: You can tailor data collection to your specific research aims e.
What is operationalization? What is hypothesis testing? What are the main qualitative research approaches? There are five common approaches to qualitative research : Grounded theory involves collecting data in order to develop new theories. Ethnography involves immersing yourself in a group or organization to understand its culture. Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
Action research links theory and practice in several cycles to drive innovative changes. How do you analyze qualitative data? There are various approaches to qualitative data analysis , but they all share five steps in common: Prepare and organize your data.
Review and explore your data. Develop a data coding system. Assign codes to the data. Identify recurring themes. What is a Likert scale? Are Likert scales ordinal or interval scales? What is the difference between a control group and an experimental group?
Do experiments always need a control group? What is blinding? What is the difference between single-blind, double-blind and triple-blind studies?
In a single-blind study , only the participants are blinded. In a double-blind study , both participants and experimenters are blinded. In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analyzing the data. Why is blinding important? What is a quasi-experiment?
When should I use a quasi-experimental design? What is simple random sampling? What is an example of simple random sampling? When should I use simple random sampling?
However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied, If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.
In practice, people definitely do refer to classification problems, e. The Elements of Statistical Learning Sign up to join this community. The best answers are voted up and rise to the top. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Learn more. Ask Question. Asked 7 years, 1 month ago. Active 6 years, 11 months ago.
Viewed 1k times. Improve this question. Do you have high correlation in your dependent variables? Also, you sure as heck can have multicollinearity in your dependent variables.
Skip to content Chapter 8: Complex Research Designs. Explain why researchers often include multiple dependent variables in their studies. Explain what a manipulation check is and when it would be included in an experiment. Researchers in psychology often include multiple dependent variables in their studies. The primary reason is that this easily allows them to answer more research questions with minimal additional effort.
When an independent variable is a construct that is manipulated indirectly, it is a good idea to include a manipulation check. This is a measure of the independent variable typically given at the end of the procedure to confirm that it was successfully manipulated. Multiple measures of the same construct can be analyzed separately or combined to produce a single multiple-item measure of that construct.
The latter approach requires that the measures taken together have good internal consistency. Practice: List three independent variables for which it would be good to include a manipulation check.
List three others for which a manipulation check would be unnecessary. Hint: Consider whether there is any ambiguity concerning whether the manipulation will have its intended effect.
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