Research Design: Robust Approaches for the Social Sciences, Essay Example

How many Independent variables are in 4 x 6 factorial designs?  How many conditions (cells) are in the design?

2 Independent variables and 24 conditions are present in the 4×6 factorial designs.

What is the difference between a cell (condition) mean and the means used to interpret a main effect?

The means of all of the separate conditions are referred to as Cell means whereas the means used to interpret a main effect are marginal means i.e., the means across the rows and down the columns.

What is the difference between a complete factorial design and an incomplete factorial design?

A complete factorial design is one that consists of all combinations of all factor-levels of each factor and has the capacity of estimating all factors and their interactions. In contrast, an incomplete design contains only a fraction of the possible combination of different levels of different factors.

Explain the difference between a two-way ANOVA and a three-way ANOVA?

Two-Way ANOVA has 2 independent variables (factors) each having multiple conditions. Three-Way ANOVA extends the Two-Way ANOVA such that one, or more, two-way interactions differ across the levels of a third variable.

What conclusions can be drawn from the F-ratios?

The conclusion we deduce from the F-ratios is that practice hours have a significant main effect on a timed task while the gender, the interaction effect of the gender and the practice hours have no consequence on the timed task.

The graph lines overlap on each other because the means are equal. Therefore, we are unable to see the graph line for male since it was overlapped by the mean line for female.

Difference between multiple independent variables and multiple levels of independent variables. Which is better?

Independent variables are used as a balancing point of research studies. These are dedicated towards measuring the different stages of development, specifically when it involves mandating a better course of situational analysis, related to the modern issues affecting the world at present. Most often than not, these issues are associated with social conditions connected to communities in particular; facing situations that possibly call for special attention.

Multiple levels of independent variables are established to discern a multi-faceted perception of measuring the different concepts of effective distinction. These are responsible to make a particular study more effective with regards to deciding the most vital issues requiring attention and especially in setting up the highly common points of development that are distinctively in need so as to create a more developed system in most communities, at present.

We can learn by the use of multiple levels of independent variables that the value of measurement among these elements could be cross-related. The fact that epitomizes this, the most, is that the independent variables are allowed to stand as a unified element contributing to the overall value of the research.

Blocking
Involving blocking elements in researches are an indicator of a distinctive approach that signifies a definitive move towards controlling the elements. These elements are ones that affect the different issues i.e. creating a better way to develop an improved sense of authorizing the effects of the study in actual situations. Practically, the need to block these elements is highly necessary so as to pin- point the more important matters as compared to those that are more inclined towards various other expected results of the research.

Blocking particular variables levies a great impact on how the studies are developed and created. We are in need of a new understanding that allows distinction of better results necessary for imposing a new system. A system, that can change the outlook of the society towards particular societal issues demanding due adjustment.

Main and Interaction Effects
Main effects of studies refer to the different results obtained through research methods applied by the researchers. However, there are certain side-effects that evidently highlight the major aspects that possibly allow changes in the society especially on matters related to the research that is on its way to being completed.

These side-effects are observed in the form of interaction effects. These effects are usually the result of matters that interact with each other especially with respect to the overall concept of development that the research intends to follow through. The interaction of different variables creates ripple-effect putting a determinable impact on the overall value of the implicated worth of the study being completed.

How does a covariate reduce noise?

Replication of results is oft considered, the primary noise that creates disturbances in most studies. Research is deemed to present a more helpful idea about what is real from what is theoretical. Understandably, it could be assumed that controlling replications is very important for ensuring the validity of the study because its purpose is to develop a higher and important value of development. We expect it to influence society’s perception with respect to different concepts about matters. Matters, such as these, are most likely reflective of elements that are required for application.  Utilizing these noises is considered effective for making sure that the different variables of the study are controlled accordingly. This shall improve the method for conducting necessary adjustments to re-establish the realistic value of each research. One of the most fundamental concepts in social research is making adjustments.

The differential process of analyzing the multiple covariance, used in a research, increases the point of comparison and determines the value of the research even further thus giving a sound indication about how elements of differences can be employed to help derive the most common points in the study. These common points can repel the assumption of weakness on how the value of improvement, included in the study, is applied in accordance to actual situations.

Fractional factorials are adopted to measure the divisible aspects of research-variable analysis. The use of fractional factorials allows the values of the different variables that constitute the research, to be analyzed consequently. They are measured according to the value that they represent in the society. This approach is used to make sure that each variable is identified efficiently in relation to the modern ways of imposing changes so as to render the implicative value of research studies.

Describe and explain three trades-offs present in experiments

The trade-off between the internal and external variables of research, help establish a better foundation for study analysis. We can understand this phenomenon by observing how modern researches are handled.  Trade-offs become highly important at the point of creating a distinct separation between the worth that each value of variable, used in the study, is identified with. Notably, trade-offs are established to aid researchers in finding a better approach towards determining the real value between elements employed during the research. These variables [upon measurement] create a certain dimension that identifies well with the validity and reliability of the study being conducted.  The trade-off of analysis between conclusions and presumptions is created through this process. Basically, the cross referencing process for these particular elements and the way they are analyzed creates an effective approach towards determining an actually effective application of the research. The conclusion that has been derived from the measurement and analysis of the presumptions, extensively commands a better core-foundation for the final determination of the value in the whole study. Trading-off the worth of the variables used in this research method lends to the understanding of how one variable relates to another and how such relation establishes a new ideal on what the study is for and how well it is able to control the changes that need to be applied in the society, as consistently derived from the results garnered from the research itself.

The primary purpose of a two-way ANOVA is to discern if there is an interaction between the two independent variables on the dependent variable. The three-way ANOVA is used to ascertain whether there is an interaction effect between three independent variables on a continuous dependent variable (i.e., in case, a three-way interaction exists). Otherwise, it extends the two-way ANOVA, which is used to make sure if such type of interaction is present between just two independent variables (i.e., rather than three independent variables).

Determining the interaction between variables in a research is very important as they would definitely determine the overall value of applicability of the research in actual situations. This hinges on the extensive idea of instructing the real worth of each variable available in the study and examined in the research.

All things considered, the contributing values that the research variables have towards one another need to be balanced as that is a very significant aspect of recreating the foundation upon which the study depends. Realistically, it should be realized that when it comes to the understanding of the most important elements that make up a research, the cross referencing of the values of different variables used to determine the strength of the method should be employed to actually understand the issues and topics included in the study.

Supposedly, the correlative association of these elements, together, helps differentiate the value of one study as a separate entity of work from another. Notably, this is how studies become more successful in contemplating the most controversial points of concern; regarding specific topics in the society. These are matters that influence the general worth of the research as a valid element. It ought to be realized that with the surfacing of assumptions like measuring the value of theories separated from the ideas of reality, it gets to be quite powerful and is emphatically seen to a degree definite in measuring how good aspects of the research could be utilized likewise.

References

Gorard, S. (2013) Research Design: Robust approaches for the social sciences, London:SAGE, Video of a lecture on research design.

Freshwater, D., Sherwood, G. & Drury, V. (2006) International research collaboration. Issues, benefits and challenges of the global network. Journal of Research in Nursing, 11 (4), pp 9295–303.

Cohen, N. &Arieli, T. (2011), Field research in conflict environments: Methodological challenges and snowball sampling. Journal of Peace Research 48 (4), pp. 423–436.

Soeters, Joseph; Shields, Patricia and Rietjens, Sebastiaan. 2014. Handbook of Research Methods in Military Studies New York: Routledge.

Hoffman A (2003) Research for Writers, pp 4-5. London: A&C Black Publishers Limited.