1.4 Imputation of Missing Data Imputation refers to the ability to predict a missing value based on information from other variables that the individual provides. Development of easy and fast sophisticated computer methods has led to the ability for various imputation methods. Algorithms for imputation include those for educated guessing; where one can make an informed "guess" about a missing value. For example, in a data matrix, if the participant responded with all 5s, then one could assume that the missing value is a 5. Average Imputation uses the average value of the responses from the other participants, for a variable, to fill in the missing value. If the average of the 40 responses on the question is a 6.5, they would use a 6.5 as …show more content…
Be that as it may, these methodologies have a strong dependence on the regression model. In the event that the incomplete data cannot be properly modelled parametrically, the method might have poor predictive power. For the most part, the true distribution of the data set is unknown, which is indispensable to the foundation of regression models. Non-parametric methods can offer unrivalled outcomes by capturing the structure in the datasets, for example in kernel-based imputation [44] and K- nearest neighbour imputation [37]. K-nearest neighbour(k-NN or KNN) imputation replaces NaNs (Na’s) in the data with the corresponding value from the nearest-neighbour column. A case is imputed using values from the k most similar cases. The nearest-neighbour column is the closest column in Euclidean distance. If the corresponding value from the nearest-neighbour column is also NaN, the next nearest column is used. In the article "An Evaluation of k-Nearest Neighbour Imputation Using Likert Data", Likert Data", Per Jönsson and Claes Wohlin report that they simulated the k-NN method with different values of k and for different proportions of missing data and state that their findings indicate that it is feasible to use the k-NN method with Likert data. They suggested that a suitable value of k is approximately the square root of the number of complete cases. They also demonstrated that even when the method rules with respect to selecting neighbours were
You have a 5-question multiple-choice test. Each question has four choices. You don’t know any of the answers. What is the experimental probability that you will guess exactly three out of five questions correctly? Type your answer below using
al.,2007). Using previously researched scholar articles and books, the authors were able to base their search, follow certain guidelines and compare their results with other results. Using tests such as the Kruskall-Wallis non-parametric test, Nagel et. al.(2007) were able to examine the differences in performance based on each grade group.
This is then done for all trials. Then, once all five values of k are found, the average is taken by adding all five values of k and dividing by 5. The experimental k average is 0.105894M/s.
1. A Likert scale (/ˈlɪkərt/[1]) is a psychometric scale commonly involved in research that employs questionnaires. It is the most widely used approach to scaling responses in survey research, such that the term is often used interchangeably with rating scale, or more accurately the Likert-type scale. One of the most common scale types is a Likert scale. A Likert scale is commonly used to measure attitudes, knowledge, perceptions, values, and behavioral changes. A Likert-type scale involves a series of statements that respondents may choose from in order to rate their responses to evaluative questions
The methods used to obtain these results were: From this text of the article I conclude that the
The below figure indicates the 5 values I’ve chosen for K between 0.5 and 1 and shows how smooth the transition is from the original value to 1.
In this chapter, I will analyse the data according to the principles proposed, such as Likert’s scale. According to the data collected, I will come out with certain conclusions to predict the respondents’
Based upon the data I was presented I feel that the grade for this assignment should
| Based on explicit knowledge and this can be easy and fast to capture and analyse.Results can be generalised to larger populationsCan be repeated – therefore good test re-test reliability and validityStatistical analyses and interpretation are
There were 37 Likert Scale statements and two open-ended questions. The Likert Scale questions were on a 1-5 scale with the lower numbers representing disagreement and the higher numbers representing agreement. Data collection occurred using a random sample of 7 teachers from varying grade levels and subjects.
Next, the researcher will use the responses of the self-reporting questionnaire to attempt to triangulate the data. If the sum total of the Likert style questions equals a 12, that indicates no effect. Anything above a 12 indicates a positive effect, anything below equals a negative effect. The data from the pretest/posttest should reflect the data from the questionnaires and thus help bolster the validity of the inferences made from the study and answer the research question: What is the effect of two weeks of disciplinary literacy instruction as a means to learn social studies content on student declarative content
For the value 10, 40, 20, 50, and 40, the value of the arithmetic mean is
1 103.5 ± 8.6 102.6 ± 6.1 103.4 ± 6.2 103.2 ± 8.6 105.2 ± 10.8 104.8 ±
At this time there is no other information that can be provided to add additional information on the missing
The Cronbach’s alpha of the sample responses came out to be as .784, which shows that our data is 78.4%. And the KMO test which is the sampling adequacy test came out to be as .691 which should be greater than .5, implies that factor analysis can be applied on this data.