In research, internal validity is described as a concept thataddresses the question of whether the independent variables causedany changes observed in the dependent variables. The four threats tointernal validity include the history, maturation, testing and thepractice effect. History entails the events taking place between themeasurements of dependent variables. Maturation refers to the changesthat happen to the participants of the study. Testing is a threatthat results from the measuring of the dependent variables. Thepractice effect benefits the study by bringing about the experiencewith the previous study.
Wheneverparticipants need to be selected, three considerations have to TheScientific, and these include their availability, precedent and thenature of the project. Availability means that the participants arechosen depending on how free they are to participate in the study.The consideration is advantageous to the participant as it does notdisrupt their normal routines. The number of participants to beinvolved in a study is dependent on the population size and theresources available to employ a larger sample size. The experimentercan be an extraneous variable if they manipulate the thinking of theselected participants. The expectations of the researcher should beclassified as is variable rather than nuisance variables. To minimizethe experimenter effects, randomization can be employed.
Expectationsof participants can sometimes act as extraneous variables. Theexperimenter may be having expectations that the research is going tobenefit them and end up doctoring the responses. Bias can result fromeither the nuisance or extraneous variables, and they are bestavoided by controlling in.
A variablecan be described as a factor in research that is subject to change.It should have as many values as possible to minimize thepossibilities of research-related bias. An operational definition, onthe other hand, can be described as a clear and detailedcharacterization of any measure. It helps researchers in determiningwhether the decision made is favourable or wrong. For example, in astudy to measure the level of happiness in a certain population, theoperational definition here can be given by the population’s scoreon the test.
Anindependent variable is a factor in research that stands alone and isnot affected by other study variables. Examples include age, sex,location and health status of individuals in the assessment ofeconomic output. Participant independent variables have a directrelationship with the participant and cannot be separated, unlike theother independent variables that can be separated from theparticipant.
Extraneousvariables should be controlled in an experiment as failure to do thismay lead to undesirable results. An extraneous variable is anundesirable factor in an experiment that influences how dependent andindependent variables relate. An example is to determine howdifferent age groups respond to a certain movie. They get exposed tolight and are given a drink[ CITATION Lau14 l 1033 ]. The lightingand the drink can be considered as extraneous variables as they areundesirable factors but affect the outcome of the experiment. Thevariables may end up confusing the researcher as they affect thedesired variables and the outcome as well.
Sometimes, aresearcher may employ more than one dependent variables in theirstudies. Some circumstances that call for more than one dependentvariable are when there are more than two research questions orobjectives. Multiple dependent variables are used when differentconstructs are being measured.
In research,it should always be of concern to assess the validity and reliabilityof the tools being used. Reliability is the extent to whichconsistent results are produced by a study tool. Validity, on theother hand, describes how accurate a measurement corresponds to theknown established facts.
Nuisance andextraneous variables can be avoided through randomization. Arandomization is an important tool as far as any research isconcerned. In randomization, study participants are selected bychance and not a choice. It is used as a control tool in theminimization of bias in an experiment. It can also eliminate the biasat all.
Elimination canalso be used to remove undesirable features in a study. It isachieved by assessing for factors that are more likely to result tobias and removing them. An example is when age as a dependentvariable is used in the assessment of exposure to hazards.
Other termsused in scientific studies include constancy, balancing, andcounter-balancing. Constancy is the process of making factors bedependable while balancing relates to the introduction of a state ofequilibrium between individuals and study factors. An example ofconstancy is seen when determining the competency of two car drivers.They get allocated to cars with similar features to eliminate anychances for bias.
Counterbalancing, on the other hand, is the neutralization of factorsby finding a proper set that outweighs each other. It is useful inthe control of order effects by presenting different treatmentsequences. Within-subject counterbalancing relates to thepresentation of different treatment sequences to the same person,whereas within-group counterbalancing entails the presentation of thevarious treatments to different subjects. We may have either completeor incomplete counterbalancing. Complete counterbalancing defines thepresentation of all possible treatment sequences while incompletecounterbalancing entails the presentation of a single set of allpossible sequences.
The fivebasic controls described above are meant to reduce the chances ofbias in an experiment to bring about validity and reliability. Ordereffects are produced when a participant is being exposed to theseries of treatments whereas carryover effect are the effects of onetreatment that are carried over to the next treatment. There are fourimportant elements of any scientific study and they includeinterleavings, recursions, iterations, and orderings ofcharacterizations and hypotheses.
We considerscience to be empirical as it contains information with empiricalevidence (information acquired by experimentation and observation).Science is self-correcting in the sense that it identifies gaps anddeficiencies, and comes up with ways to fill the gaps. This ispossible through research and experiments. There are two ways ofdescribing scientific method. It can be described as a body oftechnique that works to investigate occurrences, acquisition of newknowledge and the correction of previous knowledge. Scientific methodcan also be described as a method that is scientifically employed togather information.
Experimentalcharacteristics are important to consider when carrying out studiesand they include variables, control, participants, validity, andreliability. Experiments are valued as they provide first-handinformation, unlike the secondary sources. In scientific research, asynthetic statement gives a general outline of the idea, can be trueor false. An analytic statement is a form of an analysis, and acontradictory statement leaves the reader in a dilemma. An analyticstatement should be used to formulate a hypothesis as it bringsdifferent aspects of the research together. A general implicationform uses “if…then.” Example, if children are exposed toviolent video games, then they are bound to be aggressive.
Bothinductive and deductive forms of logic are related to reasoning.Deductive points to the multi-perspective thinking while inductive isa line of thought supported by evidence. Hypothesis testing isharmful in early stages as it has a potential for bias. It shouldinstead be conducted in the later stages of the study. A directionalhypothesis specifies the outcome of the experiment. A non-directionalhypothesis cannot predict the exact outcome. The former is used ininstances where the researcher has a clue of the outcome and thelatter is used when the researcher has no idea of the outcome.Falsibility can be used in experimental research and it describes thepossibility that a statement can be proved to be false as seen innull hypotheses.
In summary,there are a number of concepts that are important when it comes tocarrying out experimental studies. One may find themselves involvedin cross-cultural studies. It should be of importance to note thatparticipants need to be selected with care and proper randomizationperformed. The aim is to reduce the possibilities of research-relatederrors. In cross-cultural studies, a stratified sampling technique islikely to give a desirable effect as compared to random samplingtechniques. Data collection tools such as questionnaires need to bepre-tested for validity and reliability before they are put into use.Responses from cross-cultural studies should be presented with thelanguage of the respondent to avoid the distortion of informationassociated with translation.
Laura, T. (2014). Independent, Dependent, and Other Variables in Healthcare and Chaplaincy Research. Journal of Healthcare Chaplaincy, 161-170.