Hi everyone
Could you please share your recommendations, regarding the questions at the end of this post?

Research objectives:
1. What is the association between tourists' and residents' aesthetic experiences and destination aesthetic features?
Note: Aesthetic experiences are categorized into 6 types of experiences. For example, the experience of the beautiful and experience of the ugly and 4 more types of experiences.
Destination aesthetic features: a distinguished 7-point Likert semantic differential scale with 18 items. For example item 1 reads like:
I would say that the place was............ not crowded 1 2 3 4 5 6 7 crowded.
2. How often the six types of aesthetic experiences occur? (7 points Likert scale for frequency)

Variables:
Dependent variables:
1. Comprehensive descriptions of six types of aesthetic experiences. For example, the experience of the beautiful reads like "You feel you are lucky that you have the chance to enjoy and acknowledge the appealing moment of experiencing the beauty. You feel thankful, fascinated, happy, and very pleased......"
2. The frequency of occurrence of the experiences
Independent variables:
1. Residenst' district of living in the destination (5 districts)/ Tourists' city of residence (9 cities)
2. Tourist's and resident's demographic profile (Age, Gender, Education)
3. Tourists length of stay at the destination during their current travel and residents length of residency at the same destination
4. Travel frequency of tourists and residents during last year
5. Tourists' purpose of the trip (leisure, business, visiting friends and family)
6. The individual's evaluation of the Destination Aesthetic Features


I have the following research design.
Multilevel analysis: experiences are nested in individuals

Repeated measure mixed model design
Level 1: repeated measurement of the association between aesthetic experiences and destination aesthetic features
Level 2: tourists and residents


Study setting: A specific city (tourism destination)
Sample: Two groups of people (300 Tourists who travel to that specific city and 300 Residents who live in that city)
Repeated Measurement: A semantic differential scale of 18 items (18 features of a city that may make the city to be perceived as beautiful or ugly)
At the occurrence of 6 types of a specific kind of experience (e.g., the experience of beauty, the experience of ugliness, ...)

Time: Note 1: A cross-section survey is currently distributing among the target population (at a single point in time).
Note 2: Participants will answer the survey considering the occurrence of 6 types of experiences during a specific period of time. This means the residents will consider the occurrence of those experiences during the time that they have been residing in that city (e.g., some years). With the same token, tourists will consider it during the time they have been staying in the city in their current travel (e.g., some days).
Subject factor: Both within-subject factor and between-subject factor

Note A: As no study has been conducted to link the above-mentioned features of a city to those specific types of experiences, our study is exploratory and does not pose hypotheses.
Note B: The repeated measures are to be compared among the mentioned six experiences, following the principles of a within-subject design.
Note C: A cross-level interaction term (group × features of the city) will also be entered and estimated in order to compare the evaluations between tourists and residents. Please see an example of my dataset here:

Note D: Descriptions of 6 experiences and the frequency of occurrence of those experiences are dependent variables and other variables are independent.

May I sincerely ask your recommendations on:
1) How to analyze the data?
2) How should I conduct power analysis for calculating the sample size? For now, I considered collecting data from 300 tourists and 300 residents but I am not sure whether it is necessary to recruit overall 600 people or not. (Note: Some people may experience all 6 types of experiences, some may have 5 to 2 experiences and few people may have only 1 experience)
3) How should I treat missing data?

Many thanks in advance,