Research

What are the five main objectives of nursing research.

(Hint: the first letters form this acronym, EDEPI.) Explore, describe, explain, predict, and influence.

Describe the two forms of the scientific method, and explain why both are important. The two forms or styles are the inductive form and the deductive form.

(a) The inductive scientific method follows three steps: observe the world, search for a pattern in what is observed, and make a generalization about what is occurring. This is a "bottom up" approach to research. It is especially useful for generating and constructing new ideas and theories. (b)The deductive scientific method also follows three steps: state the hypothesis (based on theory or research literature), collect data to test the hypothesis, and make a decision to accept or reject the hypothesis. This is a "top down" approach to research. It is especially useful for testing ideas and theories.

What is a meta-analysis, and why is the conclusion reached in a meta-analysis study more valid than the conclusion reached in a single study?

A meta-analysis is a quantitative technique used to integrate and describe the results of a large number of quantitative research studies. It is helpful because it is based on a large number of studies rather than a single study. In other words, it provides the results of research replication.

How do research questions differ in qualitative and qualitative research, and what is their purpose?

A quantitative research question is an interrogative sentence that asks a question about the relation that exists between two or more variables. Its purpose is to identify the variables being investigated and to specify the type of relationship, descriptive, predictive, or causal, being investigated. A qualitative research question asks a question about some process, issue, or phenomenon that is to be explored. Its purpose is to give focus to what is being investigated and to identify what is being explored.

What is a representative sample, and when is it important to obtain a representative sample?

A representative sample is a sample that resembles the total population. It is important to use a sampling method that produces representative samples when your goal is to understand the characteristics of a population based on study of a sample (i.e., when you want to directly generalize from your sample to your population).

What is the difference between a statistic and a parameter?

A statistic is a numerical characteristic of a sample. A parameter is a numerical characteristic of a population.

What do all of the "equal probability selection methods" (i.e., EPSEM) have in common?

Each member of the population has an equal chance of being selected into the sample in each of these selection methods. By the way, note that simple random sampling is not the only equal probability sampling method.

Why is each of the five main objectives of research/science important?

Each of these has an important role in research and science. Exploration is especially important in the early stages of research to generate concepts and theories that can be further tested later. It gets research started; it gives us direction. Description is carried out, to some degree, in every research study; it provides needed information and helps us to understand exactly what we are looking at. Explanation is important because it studies causes and effects and it involves testing and improving theories (i.e., our explanations). Prediction is common in the mature sciences, and helps us to improve our world by predicting what will happen. For negative predictions (e.g., dropping out of school and drug use), predictions can be followed with interventions to help prevent the negative outcomes. For positive predictions, one wants to do whatever leads to the positive predictions. Influence is the ultimate goal of research as we strive for social betterment and improvement of our world; in education, influence comes about through the implementation of demonstration programs to show what works and then later through changes in educational policies to have a broader social impact.

What is meant by the term experimental control, and how is experimental control related to differential influence within the experiment?

Experimental control refers to the researcher's attempt to eliminate any differential influence of extraneous variables. In multi-group designs, the key is to eliminate the problem of differential influence of any and all extraneous variables; this is done by making the groups similar on any important extraneous variables at the start of the experiment and during the experiment (i.e., it is done by achieving experimental control). In other words, you want the extraneous variables (the bad variables that can confound or confuse your conclusions) to have a constant effect on the DV (i.e., you want to eliminate the problem of differential influence). For example, if IQ is related to the DV, you want make sure that the different groups are composed of people with similar IQ levels so that the groups will not differ on the extraneous IQ variable. Also, during the conduct of the experiment it is important to treat all groups the same (except for administration of the IV). (In the next chapter we will talk about how to obtain some control for extraneous variables in single-group and single-case experimental designs.) In multi-group designs (designs with two or more comparison groups) the goal is to make the groups the same on all extraneous variables which might have an influence on the DV through the operation of differential influence. Then we systematically vary the levels of the IV. Finally, if we did this, we will be able to conclude that the group differences that emerge are due to the IV rather than due to some extraneous variable. In short, we will be able to conclude that the IV affected the DV, and that what we observed was not due to some other variable. We will have established the causal link between the IV and DV (which is the goal of experimental research). In summary, differential influence is bad and we want to eliminate it. We eliminate it through experimental control, which is good.

How do you select a stratified sample?

First divide your sampling frame into subpopulations based on one or more stratification variable. Then you take random samples from each of these subpopulations. The sample sizes from the subpopulations will depend on whether you are using proportional stratified sampling or disproportional sampling.

What are the three steps for selecting a systematic sample?

First, determine the sampling interval; second, select a random starting point between one and k; third, select every kth element (including and starting with the element selected in step two). Note that our definition of systematic sampling includes these steps in it.

How you manipulate IV

First, the IV can be manipulated by presenting a condition or treatment to one group and withholding the condition or treatment from another group (the presence or absence technique). For example, the researcher may give a new drug to one group and a placebo (a pill with no active ingredient) to the control group. Second, the IV can be manipulated by varying the amount of a condition or variable (the amount technique). For example, the researcher may provide three levels of instruction to the participants in three groups (none, one hour, and five hours). Third, the IV can be manipulated by varying the type of the condition or treatment administered (the type technique). For example, the researcher may provide client-centered counseling to one group of depressed patients and provide rational-emotive therapy to the other group of depressed patients.

What are the different ways a researcher can use to manipulate an independent variable?

First, the IV can be manipulated by presenting a condition or treatment to one group and withholding the condition or treatment from another group (the presence or absence technique). For example, the researcher may give a new drug to one group and a placebo (a pill with no active ingredient) to the control group. Second, the IV can be manipulated by varying the amount of a condition or variable (the amount technique). For example, the researcher may provide three levels of instruction to the participants in three groups (none, one hour, and five hours). Third, the IV can be manipulated by varying the type of the condition or treatment administered (the type technique). For example, the researcher may provide client-centered counseling to one group of depressed patients and provide rational-emotive therapy to the other group of depressed patients.

What is the key difference between inductive reasoning and deductive reasoning?

Inductive reasoning is reasoning from the particular to the general. Deductive reasoning is reasoning from premises to a specific conclusion that will be true if the premises are true; it is a top-down approach to reasoning. T Quantitative research has two major subtypes: experimental and nonexperimental research. Mixed research also has two major subtypes: mixed method and mixed model research. Qualitative research has five major subtypes: phenomenology, ethnography, case study, grounded theory, and historical research.

Sampling in qualitative research is similar to which type of sampling in quantitative research?

It is similar to purposive sampling. Here is a list of the different types: · Maximum variation sampling (purposively selecting a wide range of cases) · Homogeneous sample selection (selecting a small and homogeneous case or set of cases for intensive study) · Extreme-case sampling (identifying the extremes or poles of some characteristic and then selecting cases representing these extremes for examination) · Typical-case sampling (selecting what are believed to be average cases) · Critical-case sampling (selecting what are believed to be particularly important cases) · Negative-case sampling (selecting cases that disconfirm the researcher's expectations and generalizations) · Opportunistic sampling (selecting cases when the opportunity arises) · Mixed purposeful sampling (mixing of more than one of the above sampling strategies).

What is a quasi-experimental design, and when do you use such a design?

Quasi-experimental research designs are experimental designs that do not provide for full control of extraneous variables primarily because of the lack of random assignment to groups. They are stronger than the three "weak" designs discussed in the last chapter, but they are not as strong as the five "strong" designs that we discussed in the last chapter. · You could say that they are kind of "in between" designs; they are not great, but they are not too bad either. Because they are classified as a type of experimental research, the independent variable must manipulated (although real world events that are highly similar to experimenter manipulation also may be appropriate for quasi-experimental research). You can view quasi-experiments as falling in the center of a continuum with weak experimental designs on the far left side and strong experimental designs on the far right side. (In other words, quasi designs are not the worst and they are not the best. They are in-between or moderately strong designs.) Quasi-experimental research designs are used when a) you are interested in studying cause and effect, b) you can manipulate the independent variable, c) you are not able to use a stronger experimental design because of practical or other constraints.

What is random assignment, and what is the difference between random assignment and random selection?

Random assignment is the strongest of all of the experimental control techniques; by randomly forming groups, the groups will be probabilistically equated on all known and unknown variables at the start of the experiment. As you can see, this is very powerful. Random selection is very different from random assignment. The purpose of random selection is to generate a sample that represents a larger population. The purpose of random assignment is to take a sample (usually a convenience sample) and randomly divide it into two or more groups that represent each other. Using a mirror metaphor, in random sampling, we want to sample to mirror the population, but in random assignment we simply want the different groups to mirror one another. By the way, in experimental research, random assignment is much more important than random selection; that's because the purpose of an experiment to establish cause and effect relationships.

How does random assignment accomplish the goal of controlling for the influenced of extraneous or confounding variables?

Random assignment starts with a group of research participants. Then using the process of random assignment, these participants are randomly assigned to two or more groups. Random assignment means that the researcher is taken out of the loop of making decisions about who goes into the different groups. Instead, the mathematical theory of probability is used to conduct random assignment. Because random assignment is so important, here is a little more about it...Random assignment "equates the groups" on all known and unknown extraneous variables at the start of the experiment. This makes it very plausible that any significant observed difference between the groups on the DV after the administration of the IV can be attributed to the effect of the IV. Even when you use another control technique (e.g., matching or analysis of covariance) the experimental research design is dramatically improved if random assignment is also used. Random assignment is what I (Johnson) call the "secret ingredient" of a strong experimental design. If you can include that ingredient in your research design, then include it!

If your goal is to generalize from a sample to a population, then which is more important: random selection or random assignment?

Random selection is more important in this case because you need a representative sample in order to generalize from that specific sample to the population. Note that random selection and random assignment have different purposes: · random selection is used to obtain a sample that resembles the population (i.e., to obtain a representative sample). · random assignment is used to create groups that are similar to one another.

The dependent variable

The dependent variable is a variable that is presumed to be influenced by one or more independent variables. The basic aim of an experiment is to show that changes in the manipulated IV cause changes to occur in the DV.

How do you select a simple random sample?

There are several ways: the hat model, a computer random number generator, and a table of random numbers.

When might a researcher want to use cluster sampling?

When the population is widely dispersed and you must visit the people in your sample (e.g., for in-person interviews).

Are convenience samples used very often by experimental researchers?

Yes, believe it or not, they are used most of the time in experimental research, even in strong experimental research! This, by the way, is not a problem if the experiment has random assignment and is replicated in different places at different times with different people. · Remember that the primary purpose of an experiment is make statements about cause and effect. Making statistical generalizations to populations is of secondary importance for individual experimental studies. The bottom line will be that random assignment is very important for internal validity and random selection is very important for external validity.

Research type

a)Basic research - research aimed at generating fundamental knowledge and theoretical understanding about basic human and other natural processes (b) Applied research - research focused on answering practical questions to provide relatively immediate solutions (c) Evaluation - determining the worth, merit, or quality of an evaluation object (d) Action research - applied research focused on solving practitioners' local problems (e) Orientational research - research done for the purpose of advancing an ideological position

independent variable

independent variable is a variable that is presumed to cause a change in another variable, and in experimental research, the independent variable is the variable that is manipulated by the researcher.

What are the components of a research plan, and what is contained in each component?

ntroduction (it includes a statement of the topic, problem, prior literature, statement of the research purpose, the research questions, and any hypotheses). II. Method (it includes information on the research participants, the data collection instruments, the apparatus used, if any, in the research study, and the procedure followed in carrying out the study; it may also contain a section on research design). III. Data Analysis (it includes information on how you intend on organizing and analyzing the data that you collect).

What are qualitative research?

phenomenology, ethnography, case study research, grounded theory, and historical research. Here are the definitions, with the key ideas underlined: (a) Phenomenology: a form of qualitative research in which the researcher attempts to understand how one or more individuals experience a phenomenon. (b) Ethnography: a form of qualitative research focused on describing the culture of a group of people. (c) Case study research: a form of qualitative research that is focused on providing a detailed account of one or more cases. (d) Grounded theory research: a qualitative approach to generating a theory from the data that the researcher collects. (e) Historical research: research about events in the past.